phd in computer science years

CS PhD Course Guidelines

The following program guidelines (a.k.a model pogram) serve as a starting point for a discussion with the faculty about areas of interest.   This description of the Computer Science PhD course guidelines augments the school-wide  PhD course requirements .   Students should make themselves familiar with both.

Course Guidelines for Ph.D. Students in Computer Science

We expect students to obtain broad knowledge of computer science by taking graduate level courses in a variety of sub-areas in computer science, such as systems, networking, databases, algorithms, complexity, hardware, human-computer interaction, graphics, or programming languages.

Within our school, CS courses are roughly organized according to sub-area by their middle digit, so we expect students to take courses in a minimum of three distinct sub-areas, one of which should be theory (denoted by the middle digit of 2, or CS 231). Theory is specifically required as we expect all students to obtain some background in the mathematical foundations that underlie computer science. The intention is not only to give breadth to students, but to ensure cross-fertilization across different sub-disciplines in Computer Science.

Just as we expect all students obtaining a Ph.D. to have experience with the theoretical foundations of computer science, we expect all students to have some knowledge of how to build large software or hardware systems , on the order of thousands of lines of code, or the equivalent complexity in hardware. That experience may be evidenced by coursework or by a project submitted to the CHD for examination. In almost all cases a course numbered CS 26x or CS 24x will satisfy the requirement (exceptions will be noted in the course description on my.harvard). Students may also petition to use CS 161 for this requirement.   For projects in other courses, research projects, or projects done in internships the student is expected to write a note explaining the project, include a link to any relevant artifacts or outcomes, describe the student's individual contribution, and where appropriate obtain a note from their advisor, their class instructor, or their supervisors confirming their contributions.  The project must include learning about systems concepts, and not just writing many lines of code.   Students hoping to invoke the non-CS24x/26x/161 option must consult with  Prof. Mickens ,  Prof, Kung,  or  Prof. Idreos  well in advance of submitting their Program Plan to the CHD.  

Computer science is an applied science, with connections to many fields. Learning about and connecting computer science to other fields is a key part of an advanced education in computer science. These connections may introduce relevant background, or they may provide an outlet for developing new applications.

For example, mathematics courses may be appropriate for someone working in theory, linguistics courses may be appropriate for someone working in computational linguistics, economics courses may be appropriate for those working in algorithmic economics, electrical engineering courses may be appropriate for those working in circuit design, and design courses may be appropriate for someone working in user interfaces.

Requirements

The Graduate School of Arts & Sciences (GSAS) requires all Ph.D. students to complete 16 half-courses (“courses”, i.e., for 4 units of credit) to complete their degree. Of those 16 courses, a Ph.D. in Computer Science requires 10 letter-graded courses. (The remaining 6 courses are often 300-level research courses or other undergraduate or graduate coursework beyond the 10 required courses.)

The requirements for the 10 letter-graded courses are as follows:

• Of the 7 technical courses, at least 3 must be 200-level Computer Science courses, with 3 different middle digits (from the set 2,3,4,5,6,7,8), and with one of these three courses either having a middle digit of 2 or being CS 231 (i.e., a “theory” course).   Note that CS courses with a middle digit of 0 are valid technical courses, but do not contribute to the breadth requirement.
• At least 5 of the 8 disciplinary courses must be SEAS or SEAS-equivalent 200-level courses. A “SEAS equivalent” course is a course taught by a SEAS faculty member in another FAS department. 
• For any MIT course taken, the student must provide justification why the MIT course is necessary (i.e. SEAS does not offer the topic, the SEAS course has not been offered in recent years, etc.). MIT courses do not count as part of the 5 200-level SEAS/SEAS-equivalent courses. 
• 2 of the 10 courses must constitute an external minor (referred to as "breadth" courses in the SEAS “ Policies of the Committee on Higher Degrees [CHD] ”) in an area outside of computer science. These courses should be clearly related; generally, this will mean the two courses are in the same discipline, although this is not mandatory. These courses must be distinct from the 8 disciplinary courses referenced above.
• Students must demonstrate practical competence by building a large software or hardware system during the course of their graduate studies. This requirement will generally be met through a class project, but it can also be met through work done in the course of a summer internship, or in the course of research.
• In particular, for Computer Science graduate degrees, Applied Computation courses may be counted as 100-level courses, not 200-level courses.
• Up to 2 of the 10 courses can be 299r courses, but only 1 of the up to 2 allowed 299r courses can count toward the 8 disciplinary courses. 299r courses do not count toward the 5 200-level SEAS/SEAS-equivalent courses. If two 299r’s are taken, they can be with the same faculty but the topics must be sufficiently different.
• A maximum of 3 graduate-level transfer classes are allowed to count towards the 10 course requirement.
• All CS Ph.D. program plans must adhere to the SEAS-wide Ph.D. requirements, which are stated in the SEAS Policies of the Committee on Higher Degrees (CHD) . These SEAS-wide requirements are included in the items listed above, though students are encouraged to read the CHD document if there are questions, as the CHD document provides further explanation/detail on several of the items above.
• All program plans must be approved by the CHD. Exceptions to any of these requirements require a detailed written explanation of the reasoning for the exception from the student and the student’s research advisor. Exceptions can only be approved by the CHD, and generally exceptions will only be given for unusual circumstances specific to the student’s research program.

Requirement Notes

• Courses below the 100-level are not suitable for graduate credit.
• For students who were required to take it, CS 2091/2092 (formerly CS 290a/b or 290hfa/hfb may be included as one of the 10 courses but it does not count toward the 200-level CS or SEAS/SEAS-equivalent course requirements nor toward the SM en route to the PhD.

Your program plan  must always comply  with both our school's General Requirements, in addition to complying with the specific requirements for Computer Science. All program plans must be approved by the Committee on Higher Degrees [CHD]. Exceptions to the requirements can only be approved by the CHD, and generally will only be given for unusual circumstances specific to the student’s research program

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Computer Science, Ph.D.

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We have a thriving Ph.D. program with approximately 80 full-time Ph.D. students hailing from all corners of the world. Most full-time Ph.D. students have scholarships that cover tuition and provide a monthly stipend. Admission is highly competitive. We seek creative, articulate students with undergraduate and master's degrees from top universities worldwide. Our  current research strengths  include data management and analysis, cybersecurity, computer games, visualization, web search, graphics, vision and image processing, and theoretical computer science.

This degree program offers interested students opportunities to do their research abroad, under the supervision of faculty at NYU Shanghai or  NYU Abu Dhabi .

• View the Computer Science Ph.D. program flyer
• Admissions requirements for the Ph.D. Program.
• Find out more about general  Admission Requirements .

To receive a Ph.D. in Computer Science at the NYU Tandon School of Engineering, a student must:

• satisfy a breadth course requirement, intended to ensure broad knowledge of computer science,
• satisfy a depth requirement, consisting of an oral qualifying exam presentation with a written report, to ensure the student's ability to do research,
• submit a written thesis proposal and make an oral presentation about the proposal,
• write a Ph.D. thesis that must be approved by a dissertation guidance committee and present an oral thesis defense, and
• satisfy all School of Engineering requirements for the Ph.D. degree, as described in the NYU Tandon School of Engineering bulletin, including graduate study duration, credit points, GPA, and time-to-degree requirements.

Upon entering the program, each student will be assigned an advisor who will guide them in formulating an individual study plan directing their course choice for the first two years. The department will hold an annual Ph.D. Student Assessment Meeting, in which all Ph.D. students will be formally reviewed.

Note: for pre-fall 2015 Ph.D. students, please see the pre-fall 2015 Ph.D. Curriculum.

Program Requirements

Details about Breadth and Depth Requirements, Thesis Proposal and Presentation, and Thesis Defense can be found in the NYU Bulletin.

Program Details

Each incoming Ph.D. student will be assigned to a research advisor, or to an interim advisor, who will provide academic advising until the student has a research advisor. The advisor will meet with the student when the student enters the program to guide the student in formulating an Individual Study Plan. The purpose of the plan is to guide the student’s course choice for the first two years in the program and to ensure that the student meets the breadth requirements. The plan may also specify additional courses to be taken by the student in order to acquire necessary background and expertise. Subsequent changes to the plan must be approved by the advisor.

Sample Plan of Study

In order to obtain a Ph.D. degree, a student must complete a minimum of 75 credits of graduate work beyond the BS degree, including at least 21 credits of dissertation. A Master of Science in Computer Science may be transferred as 30 credits without taking individual courses into consideration. Other graduate coursework in Computer Science may be transferred on a course-by-course basis. Graduate coursework in areas other than Computer Science can be transferred on a course-by-course basis with approval of the Ph.D. Committee (PHDC). The School of Engineering places some limits on the number and types of transfer credits that are available. Applications for transfer credits must be submitted for consideration before the end of the first semester of matriculation. 

All Ph.D. students will be formally reviewed each year in a Ph.D. Student Assessment Meeting. The review is conducted by the entire CSE faculty and includes at least the following items (in no particular order):

• All courses taken, grades received, and GPAs.
• Research productivity: publications, talks, software, systems, etc.
• Faculty input, especially from advisors and committee members.
• Student’s own input.
• Cumulative history of the student's progress.

As a result of the review, each student will be placed in one of the following two categories, by vote of the faculty:

• In Good Standing: The student has performed well in the previous semester and may continue in the Ph.D. program for one more year, assuming satisfactory academic progress is maintained.
• Not in Good Standing: The student has not performed sufficiently well in the previous year. The consequences of not being in good standing will vary, and may include being placed on probation, losing RA/GA/TA funding, or not being allowed to continue in the Ph.D. program.

Following the review, students will receive formal letters which will inform them of their standing. The letters may also make specific recommendations to the student as to what will be expected of them in the following year. A copy of each student’s letter will be placed in the student’s file.

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Academics   /   Graduate PhD in Computer Science

The doctor of philosophy in computer science program at Northwestern University primarily prepares students to become expert independent researchers. PhD students conduct original transformational research in extant and emerging computer science topics. Students work alongside top researchers to advance the core CS fields from Theory to AI and Systems and Networking . In addition, PhD students have the opportunity to collaborate with CS+X faculty who are jointly appointed between CS and disciplines including business, law, economics, journalism, and medicine.

Joining a Track

Doctor of philosophy in computer science students follow the course requirements, qualifying exam structure, and thesis process specific to one of five tracks :

• Artificial Intelligence and Machine Learning
• Computer Engineering

Within each track, students explore many areas of interest, including programming languages , security and privacy and human-computer interaction .

Learn more about computer science research areas

Curriculum and Requirements

The focus of the CS PhD program is learning how to do research by doing research, and students are expected to spend at least 50% of their time on research. Students complete ten graduate curriculum requirements (including COMP_SCI 496: Introduction to Graduate Studies in Computer Science ), and additional course selection is tailored based on individual experience, research track, and interests. Students must also successfully complete a qualifying exam to be admitted to candidacy.

CS PhD Manual Apply now

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Download a PDF program guide about your program of interest and get in contact with our graduate admissions staff.

Request info about the PhD degree

Opportunities for PhD Students

Cognitive science certificate.

Computer science PhD students may earn a specialization in cognitive science by taking six cognitive science courses. In addition to broadening a student’s area of study and improving their resume, students attend cognitive science events and lectures, they can receive conference travel support, and they are exposed to cross-disciplinary exchanges.

The Crown Family Graduate Internship Program

PhD candidates may elect to participate in the Crown Family Graduate Internship Program. This opportunity allows the doctoral candidate to gain practical experience in industry or in national research laboratories in areas closely related to their research.

Management for Scientists and Engineers Certificate Program

The certificate program — jointly offered by The Graduate School and Kellogg School of Management — provides post-candidacy doctoral students with a basic understanding of strategy, finance, risk and uncertainty, marketing, accounting and leadership. Students are introduced to business concepts and specific frameworks for effective management relevant to both for-profit and nonprofit sectors.

Career Paths

Recent graduates of the computer science PhD program are pursuing careers in industry & research labs, academia, and startups.

• Georgia Institute of Technology
• Illinois Institute of Technology
• Northeastern
• University of Pittsburgh
• University of Rochester
• University of Washington
• Naval Research Laboratory
• Northwestern University

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• Oak Ridge National Laboratory

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What Students Are Saying

"One great benefit of Northwestern is the collaborative effort of the CS department that enabled me to work on projects involving multiple faculty, each with their own diverse set of expertise.

Northwestern maintains a great balance: you will work on leading research at a top-tier institution, and you won't get lost in the mix."

— Brian Suchy, PhD Candidate, Computer Systems

What Alumni Are Saying

"In the early stage of my PhD program, I took several courses from the Department of Economics and the Kellogg School of Management and, later, I started collaborating with researchers in those areas. The experience taught me how to have an open mind to embrace and work with people with different backgrounds."

— Yiding Feng (PhD '21), postdoctoral researcher, Microsoft Research Lab – New England

Read an alumni profile of Yiding Feng

"My work at IBM Research involves bringing together symbolic and deep learning techniques to solve problems in interpretable, effective ways, which means I must draw upon the research I did at Northwestern quite frequently."

— Maxwell Crouse (PhD '21), AI Research Scientist, IBM Research

Read an alumni profile of Maxwell Crouse

The theory group here is very warm and close-knit. Starting a PhD is daunting, and it is comforting to have a community I can lean on.

— Vaidehi Srinivas, PhD Candidate, CS Theory

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Computer Science Ph.D. Program

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The Cornell Ph.D. program in computer science is consistently ranked among the top six departments in the country, with world-class research covering all of computer science. Our computer science program is distinguished by the excellence of the faculty, by a long tradition of pioneering research, and by the breadth of its Ph.D. program. Faculty and Ph.D. students are located both in Ithaca and in New York City at the Cornell Tech campus . The Field of Computer Science also includes faculty members from other departments (Electrical Engineering, Information Science, Applied Math, Mathematics, Operations Research and Industrial Engineering, Mechanical and Aerospace Engineering, Computational Biology, and Architecture) who can supervise a student's Ph.D. thesis research in computer science.

Over the past years we've increased our strength in areas such as artificial intelligence, computer graphics, systems, security, machine learning, and digital libraries, while maintaining our depth in traditional areas such as theory, programming languages and scientific computing.  You can find out more about our research here . 

The department provides an exceptionally open and friendly atmosphere that encourages the sharing of ideas across all areas. 

Cornell is located in the heart of the Finger Lakes region. This beautiful area provides many opportunities for recreational activities such as sailing, windsurfing, canoeing, kayaking, both downhill and cross-country skiing, ice skating, rock climbing, hiking, camping, and brewery/cider/wine-tasting. In fact, Cornell offers courses in all of these activities.

The Cornell Tech campus in New York City is located on Roosevelt Island.  Cornell Tech  is a graduate school conceived and implemented expressly to integrate the study of technology with business, law, and design. There are now over a half-dozen masters programs on offer as well as doctoral studies.

FAQ with more information about the two campuses .

Ph.D. Program Structure

Each year, about 30-40 new Ph.D. students join the department. During the first two semesters, students become familiar with the faculty members and their areas of research by taking graduate courses, attending research seminars, and participating in research projects. By the end of the first year, each student selects a specific area and forms a committee based on the student's research interests. This “Special Committee” of three or more faculty members will guide the student through to a Ph.D. dissertation. Ph.D. students that decide to work with a faculty member based at Cornell Tech typically move to New York City after a year in Ithaca.

The Field believes that certain areas are so fundamental to Computer Science that all students should be competent in them. Ph.D. candidates are expected to demonstrate competency in four areas of computer science at the high undergraduate level: theory, programming languages, systems, and artificial intelligence.

Each student then focuses on a specific topic of research and begins a preliminary investigation of that topic. The initial results are presented during a comprehensive oral evaluation, which is administered by the members of the student's Special Committee. The objective of this examination, usually taken in the third year, is to evaluate a student's ability to undertake original research at the Ph.D. level.

The final oral examination, a public defense of the dissertation, is taken before the Special Committee.

To encourage students to explore areas other than Computer Science, the department requires that students complete an outside minor. Cornell offers almost 90 fields from which a minor can be chosen. Some students elect to minor in related fields such as Applied Mathematics, Information Science, Electrical Engineering, or Operations Research. Others use this opportunity to pursue interests as diverse as Music, Theater, Psychology, Women's Studies, Philosophy, and Finance.

The computer science Ph.D. program complies with the requirements of the Cornell Graduate School , which include requirements on residency, minimum grades, examinations, and dissertation.

The Department also administers a very small 2-year Master of Science program (with thesis). Students in this program serve as teaching assistants and receive full tuition plus a stipend for their services.

Email forwarding for @cs.stanford.edu is changing. Updates and details here . Looking for your W-2 form?  Read Here . CS Commencement Ceremony June 16, 2024.  Learn More .

PhD Admissions | Frequently Asked Questions

Main navigation, program related questions.

• Do you have to be a Computer Science undergraduate major to apply? No, it is not required that a student have majored in CS. However, it is important that you have strong quantitative and analytical skills.
• If I already have a PhD degree in Computer Science from another institution, may I apply to the PhD program at Stanford? No, if you have a PhD in CS from another institution, you cannot apply to the CS PhD program here at Stanford.
• Are my units transferable? Units may be transferable to the PhD program towards residency credit. This determination is made via petition to the Registrar’s Office after attending our PhD program for at least one quarter. 
• Do you accept visiting scholars, exchange students, and postdocs? No. The Computer Science Department does not have such a program. All visiting scholar, exchange student, and postdoc arrangements are made between individual professors of the Universities involved.
• Where can I find housing information? You can find housing information at R&DE Student Housing .
• At the Department level, we cannot do anything to speed up this process. Foreign students are encouraged to seek a visa promptly upon receiving their I-20 because it may take up to several weeks to be processed by the U.S. Consulate due to increased security considerations.
• All new international students will be assessed a SEVIS fee in addition to other fees associated with processing visa applications. For details, visit the U.S Immigration and Customs Enforcement website.
• Does the CS department offer a MS/PhD program? No, the MS program and PhD program are two separate programs. The MS degree also does not automatically lead to a PhD degree. Applicants planning to pursue a PhD degree should apply directly to that program.
• How can I find out more about course requirements for the PhD program? See the Stanford University Bulletin for program requirements.
• How am I assigned an advisor? Each PhD student spends the first few months becoming better acquainted with the various faculty and their research areas before aligning with a faculty member to pursue their doctoral research.

Deadlines and Application Process

• Where do I get an application? External applicants and current Stanford graduate students applying to the PhD program must apply online . Current Stanford undergraduate students applying for the PhD must also apply online .
• The statement of purpose must be no more than 8,000 characters in length. This includes spaces in between words.
• What are the application requirements? Refer to the graduate application checklist .
• What is the application deadline? Check the graduate application deadlines page.
• If I previously applied, can my application be reactivated? No. We are not able to reactivate applications or supporting documents from previous applications. If you're reapplying, you must follow the same application requirements as new applicants by submitting a new online application and new supporting documents.
• What supporting documents should I send and where? No paper materials will be accepted except two sets of official transcripts (only after we contact you to submit them). Otherwise, official copies of transcripts or e-transcripts must be uploaded onto the online application. 
• Can I reapply to the PhD program? Yes, however, you cannot apply more than once for the same academic year.
• Can I get a waiver on the application fee? If you are unable to pay by credit card or if the application fee is considered to be a financial burden, see the review requirements section of the Stanford University graduate admissions website.
• Where can I list my publications and website? List all your publications and URL to your website on the supplementary form which is part of the online application. Also, list your publications and website on your resume.
• How long is the statement of purpose? The statement of purpose must be no more than two pages in length. This includes spaces in between words. Upload it to the online application.
• We recommend that you retain copies of the supporting documents that you send us and have your recommenders retain copies of what they send us. It is very important to make sure your first and last names remain consistent throughout the application process and in your correspondence with the department.
• How/when will I be notified of the admissions committee decision? The admissions office will send decision letters electronically for all applicants starting by mid-February for PhD applicants.
• The decisions are made in late February for PhD applicants.
• If I am admitted to a CS graduate program, can I defer admission? Deferrals are granted on a case by case basis and usually for only compelling reasons. Deferral petition requests are due by April 11 for PhD admits. Requests for deferrals should be sent to Jayanthi Subramanian ( [email protected] ).
• What is the GPA requirement? Typically GPA's are at least 3.6 (on a 4.0 scale) for PhD applicants and 3.5 for MS applicants.
• How do I calculate my major GPA? You have to identify all the courses you are counting towards the major requirement and find the average GPA of all those courses. If you have a double major, you need to calculate two different GPAs based on the separate group of courses that are being used to meet the requirement.
• A weighted average calculation is necessary when courses have variable credits/units structure.
• For example, if the maximum score is 100 points per course and you have six courses per semester, your unconverted scale value would be 4800 (8x6x100) for the eight quarters of the undergraduate program. If you obtained 3700 points out of the potential 4800 points, that will be your unconverted GPA.
• Do not normalize your GPA to reflect a value relative to the highest achieved aggregate score in your class/batch/year. The only exceptions are physical education and military history; these two courses can be eliminated from the calculation.
• Utilize the "additional information" section under the statement of purpose section to briefly highlight the grading system used by your institution and your relative placement in that grading scheme.
• Can I apply to start in the Winter or Spring quarter? No, we only offer admission to the Autumn quarter for PhD applicants.
• Do I need to take the Graduate Record Examination (GRE)? GRE scores are not required from PhD applicants. 
• Exception : Individuals who have completed (not only attended) a Bachelor's degree or a two-year Master's degree (or the equivalent of either degree) at a recognized institution where all instruction is provided in English. This does not apply if the courses were completed in a country where English is spoken, though not all courses were provided in English.
• Visit Stanford University's Office of Graduate Admissions website for additional information.
• How recent must my TOEFL scores be? TOEFL scores submitted to Stanford must be from a test taken within the last 24 months (two years). No scores are valid beyond the date ETS will send or resend them to schools. Tests must be taken prior to application submission and the program application deadline.
• When should I take the TOEFL? If you are taking the TOEFL tests, it is recommended that you take the tests at least six (6) weeks before the application deadline. 
• What is the TOEFL recommendation? We expect applicants to have "good" English skills.

Ph.D. in Computer Science

Ph.d. program requirements.

The PhD degree requires 72 graduate-level credits, including:

• no 5000-level CS courses
• these credits traditionally cannot be transferred in, you must actually take at least 6 credits of coursework at UVA to get a UVA PhD
• CS 8897 and CS 9897 (Graduate Teaching Instruction) cannot be used to satisfy this 24-credit requirement (but see below)
• at least 12 credits in any combination of CS 8897 and CS 9897 (Graduate Teaching Instruction), corresponding to two semesters as a full-time, 20 hour per week TA (see Chapter 3.2)
• Completion of the Qualifying Examination (see Chapter 5)
• Completion of the PhD Proposal (see Chapter 6.3)
• Completion of the Oral Defense of the written Dissertation (see Chapter 6.4)
• Finally, complete the “ Graduate Student Leave Request ” form (see Section 2.5) to leave the program.

These requirements have significant overlap with the MCS and MS degree requirements; many students choose to earn one of those Master’s degrees as part of their PhD studies.

Application Requirements

Computer science background requirements.

The Department of Computer Science does not require that applicants hold a bachelor's degree in Computer Science. However, applicants are expected to have a strong background in Computer Science. A suitable background would include courses in the following core areas:

• Data Structures
• Discrete Mathematics
• Assembly Language and Computer Organization
• Programming in a procedural language such as C, C#, C++, or Java.

Applicants are also expected to have taken several (but not necessarily all) courses in specialized areas:

• Operating Systems
• Programming Languages
• Artificial Intelligence
• Computer Networks
• Automata and Formal Languages
• Software Engineering

A year of college-level Calculus is also required. In general, experience gained working is not considered equivalent to successful completion of the courses listed above.

Grade Point Average

There is no minimum GPA required for admission. However, most applicants who are offered admission to our program have a GPA of at least 3.3 (out of 4.0). The grades in Computer Science, mathematics and related courses are more important than the overall GPA.

GRE scores are optional. 

Letters of Reference

If possible, letters of references should be written by faculty at a university previously attended. Letters of reference from Computer Science faculty are preferred, but references from employers are welcome. References should pay particular attention to academic achievements and evidence of independent, creative problem solving.

TOEFL/IELTS Scores

• If you are a permanent resident of the U.S., TOEFL is not required
• If you received a 4-year degree at an English-speaking institution (whether or not the institution is in the U.S.), TOEFL/IELTS is not required.
• If you received a 4-year degree at a non -English-speaking institution and a Master's degree from an English-speaking institution, TOEFL/IELTS is required. 
• Note that if you have a solid command of written and spoken English, TOEFL/IELTS waivers are possible! Contact via email,  [email protected] , explaining why you believe TOEFL/IELTS can be waived (include evidence such as verification of duties as a Teaching Assistant that required significant interactions in English, copies of expired TOEFL/IELTS scores, presentations at conferences in English, etc.). 

It is unusual that we offer admission to an applicant with an overall TOEFL score below 90 / IELTS below 6.5. Scores can be sent electronically to UVa at institution code B875. Some students with lower scores may be required to complete the UVA Summer English for Academic Purposes Program prior to admission.

Application Evaluation

Applications are evaluated based on the following factors:

• Background in Computer Science (including project work)
• Grade Point Average (GPA)
• Graduate Record Examination (GRE)
• Letters of reference
• Personal statement
• TOEFL/IELTS scores

Applications are evaluated in their entirety. A weakness in one factor might be mitigated by strength in another.

Financial Aid / Tuition 

Occasionally, the school of Engineering offers Master Fellowships. More information can be found on the Engineering Cost Aid webpage: https://engineering.virginia.edu/future-grads/graduate-admissions/cost-aid , and you can learn more about UVA Fellowships here: https://citizenscholars.virginia.edu/fellowships  

PhD students are usually admitted with a financial aid package in the form of a First-Year Research Assistantship that allows students to explore research with various faculty members and find their best match. It is expected that students will join a research group by the end of their first year and then be supported as a Research Assistant (RA). This financial aid package includes a competitive stipend, tuition, fees, and health insurance coverage. Details of this award are given at the time of your notification of acceptance into the Computer Science PhD program.  

You are encouraged to apply to outside sources for fellowships or you can apply for federal assistance by filling out a Free Application for Federal Student Aid .

The UVA Tuition and Fees page includes the costs per academic year by school. 

CS Admissions Frequently Asked Questions (FAQs)

How do i apply.

Please visit this Web page to apply.

When is the application deadline?

See details in the section above (Admissions).

How much does it cost to apply? Can this fee be waived?

Visit this UVA Engineering FAQ page for details on the cost to apply, and learn if your fee can be waived.

Is the TOEFL/IELTS required?

International students must have an outstanding command of the English language in order to enroll at the University of Virginia. The TOEFL/IELTS exam is required of all applicants if the language first learned and spoken in the home is not English, and they are not permanent residents. However, TOEFL/IELTS is not required if the applicant has received a 4-year degree at an English-speaking institution (whether or not the institution is in the U.S.). (If the applicant has a 4-year degree from a non-English-speaking institution and a Master's degree from an English-speaking institution, TOEFL/IELTS is still required.) It is unusual that we offer admission to an applicant with an overall TOEFL score below 90 / IELTS below 6.5. 

I scored less than 22 on the Speaking section of TOEFL. Can I still apply?

We review all applications thoroughly, along a number of dimensions. It is unusual that we offer admission to an applicant with an overall TOEFL score below 90/ IELTS score of 6.5.

Where do I send my GRE and/or TOEFL/IELTS scores?

The Institution code for School of Engineering and Applied Science of the University of Virginia for the GRE is 5820. The code for TOEFL is  B875. There is not a specific code for the Department of Computer Science.

I'm taking TOEFL/IELTS or GRE after your deadline (Dec 15). If I apply will these scores make it into my application and be seen by the admissions committee?

We will start evaluating applications soon after the Dec 15 deadline. Applicants should submit the most complete application they can, based on the information they have at the time (e.g., current test scores, even if new test scores are anticipated).Those applications that are complete will be considered first. We will continue to evaluate applications into early next year, until we have completed our offers. As we are reviewing applications, we will certainly consider updated scores as the arrive at the University of Virginia. There is no need to email us to tell us that new scores are being sent.

Should I mail or should I upload my materials with my application?

We strongly discourage applicants from mailing in any items that can be uploaded to avoid delays in your application review, and we ask that you not send duplicate copies of previously uploaded documents. If you still need to mail documents to our office, please send them to: For US Postal: Graduate School of Engineering and Applied Science Admissions P.O. Box 401103 Charlottesville, VA 22904 For UPS/FEDEX:      Graduate School of Engineering and Applied Science Admissions      1001 Emmet Street North      Room 209B Carruthers Hall      Charlottesville, VA 22903

I’ve submitted my application and all supporting materials. Why does my application status still show as incomplete?

We will fully review your application with unofficial test scores and unofficial transcripts. Your application will only show as "complete" when your application has been submitted, your official scores and transcripts have been received and all three letters of recommendations have been received. An application is complete for review with unofficial transcripts and self-reported scores, though the checklist will still show incomplete. Please note that all official transcripts are received in our main admissions office and scanned or entered into our system manually. If you feel that your materials should have been received by now, but are NOT showing up when you login to your account, please note that the Graduate Admissions Office processes a very large number of applications and it may take longer than expected for your documents/information to appear online (in your account). It is very likely that your materials have been received, but have not been loaded into our application system yet.

If I email you my information (e.g., GPA, GRE scores, etc.) before I apply, can you tell me the chance of being accepted?

The graduate admissions committee considers many factors in an application, including more than just GPA and test scores. In particular, letters of reference and your personal statement are extremely important. Therefore, we are unfortunately unable to provide any information before the committee considers your full application.

I still have other questions. Is there anyone available to help me?

Yes! For program/degree specific questions, please send an email to [email protected]. For application support and specific questions regarding the application process, please contact: Central Graduate Admissions [email protected] 434-243-0209

The information contained on this website is for informational purposes only.  The Undergraduate Record and Graduate Record represent the official repository for academic program requirements. These publications may be found here .

Computer Science (4 Year Programme) MPhil/PhD

London, Bloomsbury

The PhD programme in UCL Computer Science is a 4-year programme, in which you will work within research groups on important and challenging problems in the development of computer science. We have research groups that cover many of the leading-edge topics in computer science , and you will be supervised by academics at the very forefront of their field.

UK tuition fees (2024/25)

Overseas tuition fees (2024/25), programme starts, applications accepted.

• Entry requirements

A UK Master's degree in a relevant discipline with Merit, or a minimum of an upper second-class UK Bachelor's degree in a relevant discipline, or an overseas qualification of an equivalent standard. Work experience may also be taken into account.

The English language level for this programme is: Level 1

UCL Pre-Master's and Pre-sessional English courses are for international students who are aiming to study for a postgraduate degree at UCL. The courses will develop your academic English and academic skills required to succeed at postgraduate level.

Further information can be found on our English language requirements page.

If you are intending to apply for a time-limited visa to complete your UCL studies (e.g., Student visa, Skilled worker visa, PBS dependant visa etc.) you may be required to obtain ATAS clearance . This will be confirmed to you if you obtain an offer of a place. Please note that ATAS processing times can take up to six months, so we recommend you consider these timelines when submitting your application to UCL.

Equivalent qualifications

Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website .

International applicants can find out the equivalent qualification for their country by selecting from the list below. Please note that the equivalency will correspond to the broad UK degree classification stated on this page (e.g. upper second-class). Where a specific overall percentage is required in the UK qualification, the international equivalency will be higher than that stated below. Please contact Graduate Admissions should you require further advice.

About this degree

On this PhD programme, you will work within research groups on challenging computer science projects.

Our research groups cover leading-edge topics , and our academics are at the forefront of their field.

The research groups, the department , and the college, provide numerous opportunities to learn more about your field and the skills required to develop your research and future careers.

Who this course is for

This programme is best suited for people wishing to embark on an academic career, as well as those interested in finding work in industry. You will be assigned a first and second supervisor, who will guide you in the development of your research project and your abilities as a researcher. The research groups, the department, and the college, provide numerous opportunities for you to learn more about your field (e.g. seminars, conferences, and journal clubs) and the skills required for you to develop your research and future careers (e.g. training courses). Many of our students have had their research results published and recognised at leading international conferences during their time on the PhD programme.

What this course will give you

UCL is ranked 9th globally in the latest QS World University Rankings (2024), giving you an exciting opportunity to study at one of the world's best universities.

UCL Computer Science is recognised as a world leader in teaching and research. The department was ranked first in England and second in the UK for research power in Computer Science and Informatics in the most recent Research Excellence Framework ( REF2021 ). You will learn from leading experts with an outstanding reputation in the field. 

Code written at UCL is used across all 3G mobile networks for instant messaging and videoconferencing; medical image computing has led to faster prostate cancer diagnosis and has developed tools to help neurosurgeons avoid damaging essential communication pathways during brain surgery; and our human-centred approach to computer security has transformed the UK government's delivery of online security.

This MPhil/PhD in Computer Science is a research degree programme that will not only challenge and stimulate you, but also has the potential to lead to a varied and interesting career and introduce you to valuable contacts in academia and the industry.

The foundation of your career

Your employability will be greatly enhanced by working alongside world-leading researchers in cutting-edge research areas such as virtual environments, networked systems, human-computer interaction and financial computing. UCL's approach is multi-disciplinary and UCL Computer Science shares ideas and resources from across all departments of Faculty of Engineering Sciences and beyond. Our alumni have a successful record of finding work, or have founded their own successful start-up companies, because they have an excellent understanding of the current questions which face industry and have the skills and the experience to market innovative solutions.

Employability

UCL Computer Science graduates secure careers in a variety of organisations, including global IT consultancies, City banks and specialist companies in manufacturing industries.

The department takes pride in helping students in their career choices and offers placements and internships with numerous start-up technology companies, including those on Silicon Roundabout, world-leading companies such as Google, Skype and Facebook, and multi national finance companies, including Morgan Stanley, Deutsche Bank and JP Morgan.

Our graduates secure roles such as applications developers, information systems managers, IT consultants, multimedia programmers, software engineers and systems analysts in companies such as Microsoft, Cisco, Bloomberg, PwC and IBM.

UCL Computer Science is located in the heart of London and subsequently has strong links with industry. You will have regular opportunities to undertake internships at world-leading research organisations. We frequently welcome industry executives to observe your project presentations, and we host networking events with technology entrepreneurs.

You will also benefit from a location close to the City of London and Canary Wharf to work on projects with leading global financial companies. London is also home to numerous technology communities, for example the Graduate Developer Community, who meet regularly and provide mentors for students interested in finding developer roles when they graduate.

Teaching and learning

You are assigned a first and second supervisor who you will meet regularly. You are also assigned a research group who normally meet regularly for research seminars and related activities in the department.

You will participate in three vivas during the course of your study. These are useful feedback opportunities and allow you to demonstrate your understanding of the literature, your progress in your research and eventually, your final thesis and research. For each viva, you will be expected to produce a detailed report of your work to date and to attend a 'verbal exam' with supervisors and/or external academics/experts.

During your research degree, you will have regular meetings with your primary supervisor, in addition to contact with your secondary supervisor and participation in group meetings. Full-time study should comprise of 40 hours per week .

Research areas and structure

• Bioinformatics: protein structure; genome analysis; transmembrane protein modelling; de novo protein design methods; exploiting grid technology; mathematical modelling of biological processes
• Financial computing: software engineering; computational statistics and machine learning; mathematical modelling
• Human centred systems: usability of security and multimedia systems; making sense of information; human error and cognitive resilience
• Information security: human and organisational aspects of security; privacy-enhancing technologies; cryptography and cryptocurrencies; cybersecurity in public policy and international relations; systems security and cybercrime
• Intelligent systems: knowledge representation and reasoning; machine learning
• Media futures: digital rights management; information retrieval; computational social science; recommender systems
• Networks: internet architecture; protocols; mobile networked systems; applications and evolution; high-speed networking
• Programming Principles, Verification and Logic’: logic and the semantics of programs; automated tools for verification and program analysis; produce mathematically rigorous concepts and techniques that aid in the construction and analysis of computer systems; applied logic outreach in AI, security, biology, economics
• Software systems engineering: requirements engineering; software architecture; middleware technologies; distributed systems; software tools and environments; mobile computing
• Virtual environments: presence, virtual characters; interaction; rendering; mixed reality
• Vision and imaging science: face recognition; medical image analysis; statistical modelling of colour information; inverse problems and building mathematical models for augmented reality; diffusion tensor imaging

Research environment

UCL Computer Science is one of the leading university centres for computer science research in Europe. The department is very well-connected with research groups across the university, and is involved in many exciting multi-disciplinary research projects.

Furthermore, research groups in the department are heavily involved in collaborative research and development projects with other universities and with companies in the UK and internationally. UCL provides significant support for technology transfer, and in particular for technology start-ups, and the department has an increasingly successful record of spin-out companies including a number of spin-outs that have been acquired by Google, Facebook, Amazon, etc.

Month 0 Registration - initially MPhil registration.

Month 0-6 - General reading, directed by the supervisor, in the area of interest. This should bring you up to the sharp end of the area and allow you to appreciate what the research problems are.

Months 6-9 - More detailed reading, aimed at becoming expert enough to tackle a thesis project. A small focused project is in order here to pin the reading on. A report on the year's activities should begin to be prepared.

Month 9 - FORMAL 1ST-YEAR VIVA (10-12 for Part-time) This is the first major examination, and must take place no more than 9 months from the start date. A feedback activity. Given a read of your report, the supervisor, 2nd supervisor and an 'assessor' review the work done with the aim of providing you with proper feedback on your work. This is also a good opportunity to get feedback for the Transfer Viva and is often used as a “mock transfer”.

Months 12-18 - FORMAL TRANSFER VIVA (15-21 for Part-time) Also known as the “Upgrade Viva” - this is where you would upgrade your expected qualification from MPhil to PhD. A substantial project report is expected demonstrating the ability to conduct research, with initial research results, and a plan for completion of the work and writing of the thesis. The outcome of the viva will determine whether you are allowed to transfer registration from MPhil to PhD.

Months 24-36 - Thesis project work being tidied up and turned into a unified piece of work. Thesis writing being planned and chapters being drafted. You are now eligible for Completing Research Status

Month 36 - MOCK VIVA (48-60 for Part-time) A draft thesis and mock viva. This is to be attended by the supervisor, second supervisor and assessor and any others thought relevant. Thesis submission forms (aka Entry forms) completed and submitted.

Months 36-42 - Complete the writing of the thesis.

Month 42 - (60-72 for Part-time) Submit thesis.

See full-time summary

Accessibility

Details of the accessibility of UCL buildings can be obtained from AccessAble accessable.co.uk . Further information can also be obtained from the UCL Student Support and Wellbeing team .

Fees and funding

Fees for this course.

The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Where the programme is offered on a flexible/modular basis, fees are charged pro-rata to the appropriate full-time Master's fee taken in an academic session. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Students website: ucl.ac.uk/students/fees .

Additional costs

As each research project is unique in nature, the AFE (Additional Fee Element) is calculated on a student-by-student basis and is determined by your academic supervisor. Please contact your supervisor for further details.

A student conference and travel fund is available to students within the department to help with costs associated with attending and presenting at conferences. Applications are considered on a case-by-case basis.

For more information on additional costs for prospective students please go to our estimated cost of essential expenditure at Accommodation and living costs .

Funding your studies

UCL offers various funding opportunities for postgraduate students. Please see UCL's Scholarships website for more information.

The department offers funding for overseas and UK students. Please see the Computer Science website for more information.

Home students will have the opportunity to apply for EPSRC DTP Studentships where available.

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website .

CSC-UCL Joint Research Scholarship

Value: Fees, maintenance and travel (Duration of programme) Criteria Based on academic merit Eligibility: EU, Overseas

Deadlines and start dates are usually dictated by funding arrangements so check with the department or academic unit to see if you need to consider these in your application preparation. All applicants are asked to identify and contact potential supervisors before making an application. For more information see our How to apply page.

Please note that you may submit applications for a maximum of two graduate programmes (or one application for the Law LLM) in any application cycle.

Choose your programme

Please read the Application Guidance before proceeding with your application.

Year of entry: 2024-2025

Year of entry: 2023-2024, got questions get in touch.

Computer Science

[email protected]

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Department of Computer Science

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Computer Science

• Postgraduate study
• Research Degrees

PhD in Computer Science

You will be based in the Department of Computer Science overlooking the lake on Campus East .

You will benefit from modern offices and collaboration spaces, and well-equipped research labs with a specialist in-department team to support your requirements throughout your studies. 

We will provide you with a laptop connected to the University network, and you will have 24/7 access to your desk and workspace. Distance learning students are allocated a work desk for the duration of their stay while they are in York.

For on-campus researchers, most of your training and supervision meetings will take place on campus at the University of York, though your research may take you further afield.

PhD by distance learning

We offer the opportunity to study for a PhD by distance learning. This is available to students based in the UK and abroad, studying full-time or part-time. Our PhD by distance learning offers the same high quality of supervisory support (primarily online), and demands the same level of academic rigour as a campus-based PhD.

You will undertake your research and thesis production remotely, joining us on campus only occasionally. You will be expected to visit York at your own expense at the following stages of your study:

• Two weeks at the start of enrolment for induction, to meet your supervisor and your research group, and to meet other PhD students;
• Two one-week visits each year at important stages ('milestones') of your study (the number of visits is reduced accordingly if you are a part-time student);
• You will normally attend your PhD viva in person.

When you are not in York, you will continue to benefit from regular supervision meetings using online communication platforms, such as Zoom. Read more about how we support distance learners .

Are you an international applicant? It is important for you to note that it is your responsibility to meet any requirements for legal entry into the UK at the time of each of your visits. While the University and Department can provide supporting letters, the University cannot make any guarantees regarding entry visas or legal residence.  Read more about applying for a visa.

Entry requirements

Undergraduate and masters degrees.

The PhD in Computer Science is intended for students who already have a good first degree in Computer Science or a related field.

For entry to the PhD programme, we require at least a 2:1 undergraduate degree, or a qualification equivalent to a UK Masters degree with a minimum average grade of 60%.

We are willing to consider your application if you do not fit this profile, providing you are able to demonstrate that you have the required amount of Computer Science knowledge and experience to succeed on the programme.

English language requirements

If English is not your first language you must provide evidence of your ability.

Find out more about English Language requirements for research degrees

How to apply

Find a potential supervisor.

You should find a potential supervisor in our Department whose area of research overlaps with yours. We encourage you to contact them to discuss your research proposal before you apply. Please identify the name of your potential supervisor in your application.

On our Research web pages, you can explore our research groups which reflect the core research strengths and expertise within the Department of Computer Science. On the web page for each research group, you'll find more information about the aims and objectives of the group and the names of group members. You can use this information to identify the groups where research interests match your own.

If you have any questions or need further information, please contact [email protected] .

Submit your application

We require you to submit the following documents:

• Research proposal
• Academic transcript(s )
• Your curriculum vitae (CV)
• Personal statement
• Details of two academic referees

Your research proposal needs to outline the nature of your proposed study and give some indication of how you will conduct your research. The purpose of this exercise is to ensure that you and your potential supervisor(s) have matching research interests.

Your proposal can build on your chosen supervisor's area of work and may be prepared with the help of your chosen supervisor. It should be about 500 to 1,000 words in length, in English and in your own words. Read more about writing a research proposal .

You can apply and send all your documentation electronically through our online system. You don’t need to complete your application all at once: you can start it, save it and finish it later.

After you have applied, you can track the status of your application and view any official correspondence online. If you have applied for an advertised scholarship, decisions on funded places may take a little longer.

Applicant interviews

If we are impressed by your full application, personal statement and references, we will invite you to interview.

The interview panel will be made up of your potential supervisor(s) and another independent academic. During your interview, it is important that you demonstrate an understanding of your chosen topic and its supporting theories.

For students based outside the UK, interviews are held online via Zoom. Applicants based in the UK are offered the opportunity to attend their interview in York. If you choose to attend in person, your visit will include a tour of the Department and its facilities.

Related links Explore our PhD opportunities Research groups in the Department of Computer Science About our research degrees Applying for a research degree Funding for research degrees Information for International students Accommodation Life at York

Department of Computer Science Deramore Lane , University of York , Heslington , York , YO10 5GH , UK Tel: work 01904 325501

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PhD in Computer Science

WPI’s PhD in Computer Science has built an international reputation for research excellence over the past 40 years, providing you with extensive opportunities to work side by side with interdisciplinary researchers at the forefront of innovations that are shaping the discipline.

Value Proposition Description

Our PhD in computer science gives students immediate access to world-class laboratories and the latest in computers and software, solving real-world problems and creating groundbreaking advances in computer security, artificial intelligence, database systems, data mining, human interaction, robotics, software engineering, visualization, and image science.

In WPI’s PhD in Computer Science, you’ll be focused on solving real-world problems, from increasing computer system resilience in the face of attacks, to effective data mining that improves medical diagnoses and treatment. Exploration is encouraged for our doctorate in computer science, so you’ll take a range of courses from different areas, including essential work in theory, algorithms, and systems or networks. Then, you’ll direct your curriculum to suit your research interests and goals in areas like graphics/imaging, artificial intelligence, and databases.

Through his mobile health and sensing research, EPICC PI Emmanuel Agu is looking at the role mobile devices, smartphones, and health care apps can play in capturing important health data and biomarkers.

In our computer science PhD program, you’ll conduct advanced research with our renowned faculty members in core research groups supported by agencies like the National Science Foundation, the US Department of Education, and the US Army.

You’ll have access to our state-of-the-art research facilities offering the latest in computers and software as you pursue your doctorate in computer science. These resources, such as the Human-Robot Interaction (HRI) Lab and the Applied Logic and Security Lab, allow for creative and inspired exploration in areas like Internet privacy, next-generation user interfaces in gaming, and artificial intelligence.

At WPI, students venture deeply into the design, application, and ethics of cutting-edge technology.

At WPI, our approach means you’ll consider the additional social, ethical, and technological implications of your research and solutions so your work becomes more applicable and effective.

Areas of study at WPI are relevant in every area of industry, government, and academia, so our multidisciplinary and collaborative approach gives your research the potential to make an even greater impact in the world.

Building better cybersecurity tools, using smartphone apps to detect mental health changes, or using data to find previously unknown patterns—all things WPI computer science students do.

Our state-of-the-art facilities give students access to powerful supercomputers and to facilities that support research in computer security, artificial intelligence, database systems, human interaction in virtual environments, robotics, data mining, and more.

• Applied Logic and Security Group (ALAS)
• Artificial Intelligence Research Group (AIRG)
• Database Systems Research Group (DSRG)
• Human-Robot Interaction (HRI)
• Image Science Research Group (ISRG)
• Knowledge Discovery and Data Mining Research Group (KDDRG)
• Mobile Graphics Research Group (MGRG)
• Performance Evaluation of Distributed Systems (PEDS)
• Software Engineering Research Group (SERG)
• Theory Umbrella Group (THUG)
• Tutor Research Group (TRG)

Getting Involved

WPI actively supports many ways for you to interact with other students and the campus community through clubs, organizations, and more. Some are even designed specifically for students earning a PhD in computer science:

• Computer Science Graduate Student Organization (CS-GSO)
• Association for Computing Machinery (ACM)
• Women in Computer Science (WiCS)

Refer a Friend

Do you have a friend, colleague, or family member who might be interested in Worcester Polytechnic Institute’s (WPI) graduate programs? Click below to tell them about our programs.

When you complete your PhD in Computer Science from WPI, your interdisciplinary skill set, publication record, and professional presentations of your findings are evidence of your productivity, creativity, and accomplishments. WPI’s Career Development Center offers resources to help you stand out to potential employers and ensure your successful future. They can help you find PhD in computer science job opportunities so you can get a jump start on your career. Maybe you have specific questions about what PhD computer science salary looks like? We’re here to help answer any questions you may have.

Interested in Pursuing a Master’s in Computer Science First?

Not quite ready to pursue a doctorate in computer science? Our master’s in computer science will challenge you to utilize practical and theoretical expertise as you solve real-world problems in fields ranging from game development to data mining. Maybe you’re looking to study online? Explore our online master of science in computer science which offers the same rigorous curriculum at the convenience of your busy lifestyle.

Are You Ready to Get Started on a Computer Science Career Path?

Do you think a career in computer science fits your interests? WPI’s bachelor’s in computer science blends the technical knowledge you’ll need with the global view of how to best use your expertise to better the world. Our rigorous curriculum and collaborative faculty gives you the computer science tools you need to succeed.

Are You Looking for Basic Computer Science Experience?

If you’re someone who wants to develop an understanding of computer science without majoring in the discipline, try a minor in computer science. WPI’s minor in computer science gives you the knowledge and skills you’ll be able to apply in almost any field you enter. Having this technical understanding will help you advance in your career and is experience employers want to see.

Faculty Profiles

Emmanuel Agu is currently a professor in the computer science department at WPI having received his Masters and PhD in electrical and computer engineering at the University of Massachusetts at Amherst. His research interests are in the areas of computer graphics, mobile computing, and wireless networks. He is especially interested in research into how to use a smartphone as a platform to deliver better healthcare.

I am generally interested in  network security  and  traffic analysis , and in the challenges that arise when attempting to design security systems which are  performant ,  effective , and  usable . My interests cover:

• IoT and residential network security
• Web and cloud security
• Software security
• Malware detection and understanding
• Usable security

Professor Eltabakh’s research is in the broad area of Database Management Systems and Information Management. In particular, his work is in the areas of query processing and optimization, indexing techniques, scientific data management, and large-scale data analytics. Prof. Eltabakh is currently exploring possible extensions to both database management systems and Hadoop framework to support scientific applications and health-care systems. He is a member of the Database Systems Research Group (DSRG) and a faculty member of the Bioinformatics and Computational Biology (BCB) program.

I am a system researcher by training and am particularly passionate about designing systems mechanisms and policies to handle trade-offs in cost, performance, and efficiency for emerging applications. Since joining WPI, my group’s research has focused on improving system support and performance for machine learning (ML)-related workloads. Because ML is widely adopted in many applications, it is critical to have performant systems that can effectively train, serve, and manage ML models.

Information visualization is a powerful means for understanding data and informing human minds. As people begin to rely on visualizations to make high-impact and even life-critical decisions, there is a growing need to ensure that information can be perceived accurately and precisely.

Dr. Lee’s research interests are in information retrieval, natural language processing, social computing, machine learning, and cybersecurity over large-scale networked information systems like the Web and social media. He focuses on threats to these systems and design methods to mitigate negative behaviors (e.g., misinformation, hate speech), and looks for positive opportunities to mine and analyze these systems for developing next generation algorithms and architectures (e.g., recommender system, natural language understanding).

I am interested in computer networking and security. Given the significance of the Internet in our economy and society, I am interested in improvements and studies that can have a real-world impact. My recent work has focused on how to make both enterprise and residential networks more secure. In my research work, I am exploring ways to change the traditional computer network communication model using techniques such as software-defined networking and network function virtualization.

WPI is proud to be the recipient of not one, but two National Science Foundation Research Traineeship programs. The programs provide exceptionally talented graduate students with specialized training and funding assistance to join careers at the forefront of technology and innovation. The programs are for graduate students in research-based master's and doctoral degree programs in STEM. Learn more .

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Luddy School of Informatics, Computing, and Engineering

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Computer science is a rapidly evolving field. Position yourself at its cutting edge.

When you embark on a Ph.D. in Computer Science from IU’s Luddy School of Informatics, Computing, and Engineering in Indianapolis, you’ll be conducting research alongside expert faculty mentors. Develop new algorithms, design innovative systems, explore novel applications in your area of interest, and see your work presented at top-tier conferences and published in leading academic journals.

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Computer Science Ph.D.

Challenging and rewarding.

The Ph.D. in Computer Science is ideal for those with solid academic backgrounds who are passionate about computer science and seek to make significant contributions to the field through research and innovation, including:

• Recent graduates with a bachelor’s degree in computer science who wish to pursue a career in research or academia.
• Professionals with a master’s degree in computer science or a related field seeking to advance their research skills and expertise to pursue a career in academia, industry, or government research.
• Researchers eager to develop projects in artificial intelligence, machine learning, computer security, or robotics.
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• Industry or government researchers who want to gain expertise in specialized areas and enhance their skills to take on more advanced research roles.
• Future entrepreneurs seeking to start high-tech ventures requiring advanced knowledge and expertise in computer science research.

Well-positioned for success

Luddy Indianapolis offers the only Computer Science Ph.D. program based in Central Indiana. Anthem, Dow AgroSciences, Eli Lilly, Interactive Intelligence, and Salesforce contribute to the local employer demand for researchers with a Ph.D. in computer science. The job market for graduates with doctoral degrees in Computer Science is expected to grow. According to the U.S. Bureau of Labor Statistics, the employment of Computer and Information Research Scientists is projected to increase by 21% from 2021 to 2031, with a median pay of $131,490 per year in 2021.

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Pursuing A Part-Time Phd In Computer Science: What You Need To Know

Earning a PhD is the pinnacle of academic achievement in computer science, opening doors to research, teaching, and leadership roles. But taking 4+ years off work for a full-time program isn’t feasible for everyone.

Part-time PhD options allow professionals to attain this goal while continuing their careers.

If you’re short on time, here’s the key takeaway: Part-time CS PhD programs typically take 5-7 years to complete . They provide flexibility for working students but require diligence to balance school, research, and professional demands.

The Benefits of a Part-Time CS PhD

Progress academically without leaving your job.

A part-time PhD in Computer Science offers the unique opportunity to advance your academic career while still maintaining your professional commitments. This flexibility allows you to continue working in your current job, providing financial stability and practical application of your studies.

Balancing work and study can be challenging, but the rewards are worth it. By pursuing a part-time PhD, you can deepen your knowledge in your chosen field and make significant contributions to the advancement of computer science.

Network with faculty and peers in your field

One of the key advantages of pursuing a part-time PhD in Computer Science is the opportunity to network with esteemed faculty members and like-minded peers who share your passion for the subject. Interacting with experts in the field can provide valuable insights, guidance, and collaboration opportunities.

Attending conferences, workshops, and seminars can further expand your network and expose you to the latest developments in computer science. Building these connections can open doors to new opportunities and enhance your career prospects.

Strengthen research skills and resume

A part-time PhD program allows you to develop and refine your research skills, which are highly valued in the field of computer science. Through conducting in-depth research, analyzing data, and writing scholarly papers, you can enhance your ability to critically think, problem solve, and contribute to the body of knowledge in your area of expertise.

Moreover, having a PhD in Computer Science on your resume demonstrates your dedication, perseverance, and expertise, making you a highly sought-after candidate for both academic and industry positions.

Program Structure and Requirements

Reduced course load each semester.

Pursuing a part-time PhD in Computer Science offers flexibility in terms of course load. Unlike full-time students, part-time students typically take a reduced number of courses each semester. This allows them to balance their academic commitments with other personal and professional responsibilities.

By taking fewer courses at a time, part-time students can focus on their coursework more effectively and ensure a better understanding of the material.

Original dissertation research

The cornerstone of a part-time PhD program in Computer Science is the dissertation research. Students are required to embark on an original research project under the guidance of a faculty advisor. This research should contribute to the existing body of knowledge in the field and demonstrate a deep understanding of a specific area of computer science.

The research can involve developing new algorithms, designing innovative software systems, or exploring cutting-edge technologies.

Qualifying exams and proposal defense

Part-time PhD students in Computer Science are typically required to pass qualifying exams to demonstrate their readiness for conducting research. These exams assess the student’s knowledge and understanding of the core concepts in the field.

Once the exams are passed, students need to prepare a research proposal outlining the objectives, methodology, and expected contributions of their dissertation. The proposal is then defended in front of a committee of faculty members who evaluate its feasibility and significance.

It’s important to note that the specific structure and requirements of a part-time PhD program in Computer Science may vary depending on the institution. It is advisable to consult the program’s official website or contact the program coordinator for more detailed information.

Finding the Right Program

When pursuing a part-time PhD in Computer Science, finding the right program is crucial for success. Here are some key factors to consider:

On-campus and online options

One of the first decisions to make is whether to pursue your PhD on-campus or online. On-campus programs offer the benefit of face-to-face interactions with professors and fellow students, while online programs provide flexibility for those who are working or have other commitments.

It’s important to weigh the pros and cons of each option and choose the one that aligns best with your lifestyle and goals.

Focus on faculty research expertise

Another important factor to consider when choosing a program is the faculty’s research expertise. Look for programs where the faculty members have research interests and expertise that align with your own.

This will ensure that you receive guidance and mentorship from experts in your field of interest. Additionally, professors with strong research backgrounds can provide valuable networking opportunities and connections in the industry.

Funding availability

Funding is a significant consideration for many part-time PhD students. Look for programs that offer funding options such as scholarships, grants, or assistantships. These can help alleviate the financial burden and allow you to focus on your studies.

It’s also worth exploring external funding opportunities from organizations or government agencies that support research in your field.

Managing Your Time Effectively

Stay organized with schedules and goals.

When pursuing a part-time PhD in computer science, time management becomes crucial. It is important to create a schedule that includes dedicated study hours, research time, and coursework completion. By setting goals for each week or month, you can track your progress and ensure that you are staying on track.

One effective strategy is to use a planner or a digital calendar to keep track of deadlines, meetings, and other important events. By having a visual representation of your commitments, you can prioritize your tasks and allocate time accordingly.

Additionally, breaking down larger tasks into smaller, manageable chunks can help you stay organized and prevent overwhelm. By setting realistic goals for each study session, you can make progress towards your PhD while still managing other responsibilities.

Communicate needs clearly at work

When pursuing a part-time PhD, it is essential to communicate your needs with your employer or colleagues. Letting them know about your academic commitments and the time required for your studies can help them understand your availability and make necessary adjustments.

Consider having a conversation with your supervisor or manager to discuss your situation and explore potential flexible working arrangements. This could include adjusting your work schedule, reducing your workload, or even exploring opportunities for research collaboration between your job and your PhD.

Open and honest communication can go a long way in ensuring that both your work and academic responsibilities are managed effectively.

Leverage support systems

Pursuing a part-time PhD can be challenging, but you don’t have to do it alone. It is crucial to leverage the support systems available to you.

Reach out to your academic advisor or supervisor for guidance and support. They can provide valuable insights on managing your time, selecting courses, and balancing your academic and work commitments.

Additionally, consider joining or forming study groups with fellow part-time PhD students. Collaborating with others who are facing similar challenges can provide a sense of camaraderie and support. You can share study materials, discuss research ideas, and offer each other encouragement along the way.

Lastly, don’t forget about the support of your family and friends. Let them know about your academic journey and the challenges you may face. Their understanding and encouragement can help you stay motivated and focused on your goals.

Remember, pursuing a part-time PhD in computer science requires dedication, discipline, and effective time management. By staying organized, communicating your needs, and leveraging support systems, you can successfully navigate this exciting academic journey while maintaining a balance with your work and personal life.

Completion, Careers and Next Steps

Job prospects post-phd.

Completing a part-time PhD in computer science opens up a world of exciting job prospects. With a doctoral degree in this field, you are well-equipped to pursue highly specialized positions in both industry and academia.

The demand for computer science professionals continues to grow, and obtaining a PhD can give you a competitive edge in the job market. According to the Bureau of Labor Statistics, the employment of computer and information research scientists is projected to grow 15 percent from 2019 to 2029, much faster than the average for all occupations.

This means that there will be ample opportunities for individuals with advanced degrees in computer science.

Potential teaching and research roles

One of the key benefits of earning a PhD in computer science is the opportunity to pursue teaching and research roles. Many universities and research institutions are constantly seeking experts in the field to join their faculty and contribute to cutting-edge research.

As a PhD holder, you can become a professor, teaching and mentoring the next generation of computer scientists. Additionally, you can engage in research projects, pushing the boundaries of knowledge in the field and making significant contributions to the advancement of technology.

The opportunity to share your expertise and make a lasting impact in the academic community is truly rewarding.

Higher salaries and senior positions

Earning a PhD in computer science can also lead to higher salaries and senior positions. With the advanced knowledge and skills gained during your doctoral studies, you become a valuable asset to companies and organizations.

Employers often recognize the expertise and dedication required to complete a PhD, and are willing to offer higher salaries to attract and retain top talent. In addition, holding a doctoral degree can open doors to senior management and leadership positions, where you can have a greater influence on strategic decisions and shape the direction of the company.

According to a survey conducted by the National Association of Colleges and Employers, computer science PhD graduates earned an average starting salary of $123,000 in 2020, significantly higher than those with a bachelor’s or master’s degree.

While requiring diligence and time management skills, part-time computer science PhD programs make this high-level credential attainable for busy professionals. From strengthening your research abilities to opening new career doors, the long-term benefits of earning a PhD on a flexible schedule are immense.

If you’re willing to balance work, research, and coursework, a part-time CS PhD can help you achieve your pinnacle academic and career aspirations.

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Master’s in Data Science

This collaborative degree program is jointly owned by Computer Science and Engineering, the Department of Statistics, the School of Information, and the Department of Biostatistics. The Master’s in Data Science is designed to require every student to receive balanced training in statistical skills and computational skills, combining the educational strengths of the four departments. Graduates of this program are expected to understand data representation and analysis at an advanced level.

With the MS in Data Science all students will be able to: identify relevant datasets, apply the appropriate statistical and computational tools to the dataset to answer questions posed by individuals, organizations or governmental agencies, design and evaluate analytical procedures appropriate to the data, and implement these efficiently over large heterogeneous data sets in a multi-computer environment.

The program is administered by the College of LSA, and detailed program and admissions information can be found on their website .

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A delicate touch: teaching robots to handle the unknown

William Xie, a first-year PhD student in computer science, is teaching a robot to reason how gently it should grasp previously unknown objects by using large language models (LLMs). 

DeliGrasp , Xie's project, is an intriguing step beyond the custom, piecemeal solutions currently used to avoid pinching or crushing novel objects. 

In addition, Deligrasp helps the robot translate what it can 'touch' into meaningful information for people. 

"William has gotten some neat results by leveraging common sense information from large language models. For example, the robot can estimate and explain the ripeness of various fruits after touching them." Said his advisor, Professor Nikolaus Correll . 

Let's learn more about DeliGrasp, Xie's journey to robotics, and his plans for the conference Japan and beyond. 

How would you describe this research? 

As humans, we’re able to quickly intuit how exactly we need to pick up a variety of objects, including delicate produce or unwieldy, heavy objects. We’re informed by the visual appearance of an object, what prior knowledge we may have about it, and most importantly, how it feels to the touch when we initially grasp it. 

Robots don’t have this all-encompassing intuition though, and they don’t have end-effectors (grippers/hands) as effective as human hands. So solutions are piecemeal: the community has researched “hands” across the spectrum of mechanical construction, sensing capabilities (tactile, force, vibration, velocity), material (soft, rigid, hybrid, woven, etc…). And then the corresponding machine learning models and/or control methods to enable “appropriately forceful” gripping are bespoke for each of these architectures.

Embedded in LLMs, which are trained on an internet’s worth of data, is common sense physical-reasoning that crudely approximates a human’s (as the saying goes: “all models are wrong, some are useful”). We use the LLM-estimated mass and friction to simplify the grasp controller and deploy it on a two-finger gripper, a prevalent and relatively simple architecture. Key to the controller working is the force feedback sensed by the gripper as it grasps an object, and knowing at what force threshold to stop—the LLM-estimated values directly determine this threshold for any arbitrary object, and our initial results are quite promising.

How did you get inspired to pursue this research?

I wouldn’t say that I was inspired to pursue this specific project. I think, like a lot of robotics research, I had been working away at a big problem for a while, and stumbled into a solution for a much smaller problem. My goal since I arrived here has been to research techniques for assistive robots and devices that restore agency for the elderly and/or mobility-impaired in their everyday lives. I’m particularly interested in shopping (but eventually generalist) robots—one problem we found is that it is really hard to determine, let alone pick ripe fruits and produce with a typical robot gripper and just a camera. In early February, I took a day to try out picking up variably sized objects via hand-tuning our MAGPIE gripper’s force sensing (an affordable, open-source gripper developed by the Correll Lab). It worked well; I let ChatGPT calibrate the gripper which worked even better, and it evolved very quickly into DeliGrasp.

What would you say is one of your most interesting findings so far?

LLMs do a reasonable job of estimating an arbitrary object’s mass (friction, not as well) from just a text description. This isn’t in the paper, but when paired with a picture, they can extend this reasoning for oddballs—gigantic paper airplanes, or miniature (plastic) fruits and vegetables.

With our grasping method, we can sense the contact forces on the gripper as it closes around an object—this is a really good measure of ripeness, it turns out. We can then further employ LLMs to reason about these contact forces to pick out ripe fruit and vegetables!

What does the day-to-day of this research look like?

Leading up to submission, I was running experiments on the robot and picking up different objects with different strategies pretty much every day. A little repetitive, but also exciting. Prior to that, and now that I’m trying to improve the project for the next conference, I spend most of my time reading papers, thinking/coming up with ideas, and setting up small, one-off experiments to try out those ideas.

How did you come to study at CU Boulder? 

For a few years, I’ve known that I really wanted to build robots that could directly, immediately help my loved ones and community. I had a very positive first research experience in my last year of undergrad and learned what it felt like to have true personal agency in pursuing work that I cared about. At the same time I knew I’d be relocating to Boulder after graduation. I was very fortunate that Nikolaus accepted me and let me keep pursuing this goal of mine.

It’d be unfathomable if I could keep doing this research in academia or industry, though of course that would be ideal. But I’m biased toward academia, particularly teaching. I’ve been teaching high school robotics for 5 years now, and now teaching/mentoring undergrads at CU—each day is as fulfilling as the first. I have great mentors across the robotics faculty and senior PhD students we work in ECES 111, a giant, well-equipped space that 3 robotics labs share, and it’s great for collaboration and brainstorming. 

What are your hopes for this international conference (and what conference is it?)

The venue is a workshop at the 2024 International Conference on Robotics and Automation (ICRA 2024), happening in Yokohama, Japan from May 13-17. The name of the workshop is a mouthful: Vision-Language Models for Navigation and Manipulation (VLMNM).

A workshop is detached from the main conference, and kind of is its own little bubble (like a big supermarket—the conference—hosting a pop-up food tasting event—the workshop). I'm really excited to meet other researchers and pick their brains. As a first-year, I’ve spent the past year reading papers from practically everyone on the workshop panel, and from their students. I’ll probably also spend half my time exploring (eating) around the Tokyo area.  

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• Nikolaus Correll

A robotic gripper holds various objects. On the left, DeliGrasp allows objects to be held without deforming them by using an LLM to reason about their physical properties and hold them with appropriate delicacy. 

William Xie

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Computer Science PhD Student Chosen for FASPE Ethics Fellowship

The FASPE curriculum takes advantage of the power of place with daily seminars and dialogue at sites of historic importance, often specific to their profession. The experience of the D&T Fellows is enhanced by traveling alongside the Business and Law fellows, who – in formal and informal settings – consider together how ethical constructs and norms in their respective professions align and differ.

“By educating students about the causes of the Holocaust and the power of their chosen professions, FASPE seeks to instill a sense of professional responsibility for the ethical and moral choices that the Fellows will make in their careers and in their professional relationships,” said David Goldman, FASPE’s Chairman.

As a PhD student in Computer Science, Merz Hoffmeister research is focused on robotics, building on a foundation in Computer Science, Physics, and Mathematics from the University of Colorado Boulder. His research interests include task and motion planning for tool use, online planning and plan adaptation under uncertainty, and emergency situation planning. Merz Hoffmeister has contributed to developing a real-time robotics framework for healthcare, leveraging Large Language Models for action optimization. He has also worked on projects for robotic learning via verbal feedback and torque-aware trajectory planning, demonstrating a commitment to practical and theoretical advancements in robotics.

Thinking ahead to the upcoming fellowship trip, Merz Hoffmeister says, “My keen interest in the ethical implications of robotics, shaped by personal and community experiences with job insecurity and automation's broader impacts, draws me to FASPE. I see acceptance into the program as crucial for deepening my understanding of balancing technological innovation with ethical responsibility, and for guiding and emphasizing my commitment to develop robotics that consider societal impacts and ensure equitable technological progress.”

Merz Hoffmeister joins a diverse group of 84 FASPE fellows across all six programs who were chosen through a competitive process that drew applicants from across the U.S. and the world. FASPE covers all program costs, including travel, food and lodging.

Each year, Fellowship cohorts are led by FASPE professionals; two Faculty members (scholars and/or practitioners), and partners on the ground in Germany and Poland. The D&T Program will be led by Mary Gray, Fellow at Harvard University's Berkman Klein Center for Internet and Society and Senior Principal Researcher at Microsoft Research, and Lindsey Cameron, Assistant Professor of Management, at the Wharton School, University of Pennsylvania.

FASPE maintains long-term relationships with its fellows to sustain a commitment to ethical behavior and to provide a forum for continued dialogue. To date, FASPE has over 830 alumni.

College of Engineering

The Master of Science in Robotics program at Northeastern looks at this fundamentally interdisciplinary field from three connected angles: mechanical engineering, electrical and computer engineering, and computer science. Students gain a comprehensive understanding of the algorithms, sensors, control systems, and mechanisms used in robotics to help them stand out in the field and make a transformative impact on society.

The Master of Science in Robotics program at Northeastern looks at this fundamentally interdisciplinary field from three connected angles: mechanical engineering, electrical and computer engineering, and computer science. Students select a concentration and gain a comprehensive understanding of the algorithms, sensors, control systems, and mechanisms used in robotics to help them stand out in the field and make a transformative impact on society. They can further specialize their degree with flexible electives in a variety of areas, such as mechatronic systems, robot mechanics, control systems, robotic manipulation, artificial intelligence, sensing and navigation, mobile and field robots, medical robotics, and machine learning.

Classes in this multidisciplinary program incorporate direct interaction with a variety of robotic systems supported by highly accomplished faculty, state-of-the art equipment, and advanced laboratories and research centers including the university-wide  Institute for Experiential Robotics  located in the new  EXP building . Research opportunities are available with a variety of robotic systems, including an autonomous Lincoln MKZ car, multiple deep-rated autonomous underwater vehicles, dozens of unmanned aerial and ground robotic systems, commercial and research manipulators, and biologically   inspired robots.

Students can pursue the MS thesis option or coursework only option. Upon graduating, students will be prepared for engineering jobs in the growing field of robotics, or will progress into a doctoral degree in robotics or related multidisciplinary areas across computer science, mechanical, electrical, and computer engineering.

Students with academic or career backgrounds in computer science or mechanical, electrical, and computer engineering are well suited for this program, and will take advanced core courses in all these areas.  

More Details

Unique features.

• Interdisciplinary program giving students a skill set that can evolve over time to suit changing research and career interests in this rapidly evolving industry
• Flexibility to further specialize with electives in areas such as mechatronic systems, robot mechanics, control systems, robotic manipulation, artificial intelligence, sensing and navigation, mobile and field robots, medical robotics, and machine learning
• Direct classroom interaction with quality robotics systems supported by state-of-the art equipment and advanced laboratories
• Comprehensive research with accomplished faculty, facilities, and multidisciplinary research centers, including the Institute for Experiential Robotics
• Top-ranked co-op program enabling students to gain up to eight months of professional experience as part of the academic curriculum
• Location is a robotics hub with Northeastern playing a large role educating tomorrow's leaders 
• Opportunity to pursue industry careers or progress into a doctoral degree program in robotics or related multidisciplinary areas
• Choose the MS thesis option or the coursework only option

Program Objectives

• Looking at this fundamentally interdisciplinary field from three connected angles—mechanical engineering, electrical and computer engineering, and computer science—students gain a comprehensive understanding of the algorithms, sensors, control systems, and mechanisms used in robotics to help them stand out in the field and make a transformative impact on society. 
• Upon program completion, students will be equipped with an interdisciplinary skill set that can evolve over time to suit their changing research and career interests in this rapidly evolving industry.
• Students will be prepared for engineering jobs in the growing field of robotics, or will progress into a doctoral degree in robotics or related multidisciplinary areas across computer science or mechanical, electrical, and computer engineering.

Career Outlook

• According to  Precedence Research , the global robotics technology market size was estimated at $72.17 billion in 2022 and is expected to surpass around $283.19 billion by 2032 with a registered compound annual growth rate of 14.7% during the forecast period 2023 to 2032.
• The job market for electrical and computer engineers, mechanical engineers, and computer scientists, which includes robotics, is forecasted to grow at 5%, 10%, and 23%, respectively, from 2022 to 2032, according to the U.S. Bureau of Labor Statistics.
• The Boston area is a hub for robotics research and industry—including Amazon Robotics, Teradyne, and Bluefin Robotics—and Northeastern is proud to play a large role in educating tomorrow’s leaders in this emerging area.

Learning Outcomes

Mechanical Engineering Concentration

• An ability to identify, formulate, and solve complex engineering/scientific/quantitative problems.
• An ability to explain and apply engineering design principles, as appropriate to the program’s educational objectives.
• An ability to produce solutions that meet specified end-user needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
• An ability to recognize the tools and principles needed for understanding robotic and control systems by merging electrical and mechanical engineering and computer science.

Electrical and Computer Engineering Concentration

• An ability to recognize the tools and principles needed for understanding robotic and control systems with a multidisciplinary approach that combines electrical engineering, mechanical engineering, and computer science.
• An ability to understand system-level design of complex software and hardware that is used to build robotic systems that include a variety of asynchronous sensors and actuators.
• An ability to understand the theoretical principles underlying localization, mapping, and planning to build, design, and deploy a variety of robotic systems ranging from fully autonomous to remotely operated systems.

Testimonials

—james myers, ms, electrical and computer engineering, —hanumant singh, professor, electrical and computer engineering, —amanda zhu, ms, computer engineering, looking for something different.

A graduate degree or certificate from Northeastern—a top-ranked university—can accelerate your career through rigorous academic coursework and hands-on professional experience in the area of your interest. Apply now—and take your career to the next level.

Program Costs

Finance Your Education We offer a variety of resources, including scholarships and assistantships.

How to Apply Learn more about the application process and requirements.

Requirements

• Completed online application form
• Application fee
• Two letters of recommendation
• Transcripts from all institutions attended
• GRE is not required for terms starting during the 2021-2022, 2022-2023, or 2023-2024 academic years
• Statement of purpose
• TOEFL, IELTS, or Duolingo for international applicants

Are You an International Student? Find out what additional documents are required to apply.

Admissions Details Learn more about the College of Engineering admissions process, policies, and required materials.

Admissions Dates

Applications received after the stated deadline dates will be accepted and processed as quickly as possible; however it may not be possible to have a decision rendered in time for the applicant to begin taking classes for the desired term if admitted.

Applications submitted by the referenced dates will receive full consideration for the referenced term. Applications received after the referenced dates will be considered on a case-by-case basis.

Industry-aligned courses for in-demand careers.

For 100+ years, we’ve designed our programs with one thing in mind—your success. Explore the current program requirements and course descriptions, all designed to meet today’s industry needs and must-have skills.

View curriculum

Northeastern combines rigorous academics with experiential learning and research to prepare students for real-world engineering challenges. The cooperative education program, also known as “co-op,” is one of the largest and most innovative in the world, and Northeastern is one of only a few that offers a co-op program for graduate students. Through this program, students gain professional industry experience in their field of interest as part of the academic curriculum while employed from four to eight months in a wide variety of organizations, from large companies to entrepreneurial start-ups.   In 2019, the Graduate School of Engineering placed nearly 1000 students in co-op positions. We have a team that prepares students for the cooperative education experience through resumé building, developing interview skills, and guiding professional development.

Our Faculty

Northeastern University faculty represents a broad cross-section of professional practices and fields, including finance, education, biomedical science, management, and the U.S. military. They serve as mentors and advisors and collaborate alongside you to solve the most pressing global challenges facing established and emerging markets.

Rifat Sipahi

Lawson Wong

Hanumant Singh

By enrolling in Northeastern, you’ll gain access to students at 13 campus locations, 300,000+ alumni, and 3,000 employer partners worldwide. Our global university system provides students unique opportunities to think locally and act globally while serving as a platform for scaling ideas, talent, and solutions.

Below is a look at where our Engineering alumni work, the positions they hold, and the skills they bring to their organization.

Where They Work

• GE Aviation
• Bose Corporation

What They Do

• Engineering
• Business Development
• Program and Project Management
• Entrepreneurship

What They're Skilled At

• Project Management
• Manufacturing

Learn more about Northeastern Alumni on  Linkedin .

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