data science phd oxford

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• EPSRC Centre for Doctoral Training in Health Data Science

EPSRC Centre for Doctoral Training in Healthcare Data Science

Course structure

Research & ethics, student experiences, follow us @hdscdt.

Insights derived from the analysis of large, complex data sets will make significant contributions to the prevention and treatment of disease. The aim of this doctoral training  programme  in Healthcare Data Science is to offer systematic training in statistics, machine learning, and data management. Core to the entire  programme  is to combine this technical training with a foundation in ethics.  

Ethics plays a central role in health data science, and our approach to doctoral training reflects this. Ethics and research responsibility is a vertical theme running through the four years of the  programme . Each of the first two terms begins with a week of training in ethics, responsible research and innovation, and collaborative working. In the first term, this training addresses ethical issues in data science and big data in general. In the second, it focuses upon specific ethics and governance issues in health data science and healthcare delivery.  

This EPSRC Centre for Doctoral Training in Healthcare Data Science  is located in  the Big Data Institute/Oxford Population Health Building at the University of Oxford.

ENTRY REQUIREMENTS

A data science subject degree including Mathematics, Statistics, Engineering Science, Computer Science or a related field with substantial mathematical background. Applicants are recommended to have completed an MSc in one of the above subjects.  

How to apply

We're delighted that this programme has been renewed as the EPSRC CDT in Healthcare Data Science for another five cohorts starting from October 2024. Please see the admissions page on the University website for information about entry this autumn.

This course is taking part in a continuing pilot programme to improve the assessment procedure for graduate applications, to ensure that all candidates are evaluated fairly. For this course, the socio-economic data you provide in the application form will be used to contextualise the shortlisting and decision-making processes where it has been provided. Please carefully read the instructions concerning submission of your CV/résumé, statement of purpose, transcript and letters of support from referees in the  How to apply  section of this page as well as the  full details about this pilot .

It is important that you follow these new steps for your application to be considered.  Please use the standardised CV template provided and do not upload your own personalised version as these will not be reviewed by the Directorate.

Please ignore the section that states referees should anonymise their references, this applied to other courses on the pilot scheme but not ours.

We suggest considering Reuben College  or Kellogg College as the CDT has forged partnerships with these colleges. You are of course free to select any college on your application form but the CDT encourages you to consider one of these two listed colleges.

RESEARCH ENVIRONMENT

The Centre is hosted within the Big Data Institute (BDI)/Oxford Population Health (OxPop) Building, a purpose- built building  at the heart of the University of Oxford's biomedical campus. The Big Data Institute is an analytical hub for multi-disciplinary working at Oxford, connecting world-leading expertise in statistics, computer science, and engineering to data-driven research in clinical medicine and population health. It is also home to the  Ethox  Centre , a world-leading  centre  for clinical and research ethics, and the   Oxford Centre for Ethics and Humanities . 

The building hosts the clinical informatics and big data activity of the National Institute for Health and Care Research (NIHR) Oxford Biomedical Research Centre (BRC), a substantial  programme  of translational research, delivered by the University in partnership with Oxford University Hospitals (OUH) NHS Foundation Trust .  CDT students will have the opportunity to contribute to the work at the BRC, to access the expertise of the team, and to become involved in multi- centre  research collaborations.  

The BDI/OxPop Building is also home to UK Biobank , a major national and international resource for health research. The Biobank team are leading the development of tools for the acquisition, processing, analysis, and re-use of data from clinical and online assessments, imaging, sensors, genotyping, and national datasets (including hospital episodes, death, and primary care) for a cohort of 500,000 participants. CDT students will have the opportunity to access the expertise of the team, and to become involved in Biobank-based research.  

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Machine Learning and Data Science

• CIMDA at Oxford
• More About Us

The research areas of the Machine Learning and Data Science group include deep learning, machine learning, reinforcement learning, optimisation, topological data analysis, and random matrix theory.  

Data science is an inherently interdisciplinary research area, both crossing academic disciplines and tying in with the various research groups with in the Mathematical Institute.  Members of the Mathematical Data Science group are also members of other research groups across the applied and fundamental mathematics spectrum. 

Information on courses, events, and seminars aligned with the data science research group are available on the tabs to the left of this text.

The Mathematical Institute is a founding mathematical partner of the  Alan Turing Institute, the UK’s national data science institute.

Members of the Mathematical Data Science group are also leading the following large data science initiatives:

• Centre for Topological Data Analysis
• CIMDA@Oxford

 Further information on the data science research of our faculty is available here

  https://www.maths.ox.ac.uk/groups/ml-and-ds/more-about-us

• OII >  

MSc in Social Data Science

Page Contents

Introduction, key information, student experience, supervisors, fees & funding.

The multi-disciplinary MSc in Social Data Science equips students with applied expertise in rapidly advancing domains in machine learning coupled with theories, practices, and research focus from the social sciences.

With the rapid expansion of big data and artificial intelligence (AI) in society there is a need both to understand how to best make use of these tools and approaches, as well as to consider their social implications from a practical and grounded perspective. These new approaches can provide new perspectives on classic questions in political science, law, or sociology. At the same time, the technologies behind these approaches are rapidly posing new questions of their own regarding identity, ethics, privacy, relationships, human rights, commerce, and health, with importance for societies, regulatory bodies, and states.

During this degree, students will collect, combine, and interrogate social and behavioural data from a variety of social science perspectives with an emphasis on quantitative and computational skills alongside best practices in scientific inquiry and ethical research. The course is administered by the Oxford Internet Institute within the Department of Social Science with additional teaching and supervision from faculty in departments across the university including Mathematics, Engineering Sciences, and Statistics, as well as Linguistics, Economics, and Sociology.

Students will join a cohesive cohort and will be expected to dedicate around 40 hours to this course each week during term, and to undertake further study and complete assessments during termly vacation periods. During Michaelmas and Hilary Terms, this equates to roughly 10 and 15 hours each week for each course taken.

Social Data Science students take five compulsory foundation papers, a data science intensive with three modules, and two options papers. Students finish by submitting a thesis of up to 15,000 words on topic chosen by the student in consultation with their thesis supervisor.

• Foundation papers cultivate core skills, methods, theories and concepts required for sophisticated study in the field.
• The Introduction to Data Science and Machine Learning paper consists of three short intensive courses designed to introduce programming skills for data capture and cleaning, fundamentals of statistical and machine learning, and approaches for scaling up data collection and analyses.
• Option papers enable students to develop in-depth specialist techniques and disciplinary expertise.
• The thesis assesses a student’s ability to complete an empirical research project, providing a realistic example of the challenges faced in data science settings in academia and industry.

The programme combines traditional lectures with computer lab sessions and hands-on mathematics and programming exercises.

The MSc in Social Data Science is designed for:

• Social science students with existing quantitative and programming skills who wish to further develop their skills for analysing structured and unstructured data using advanced computational and statistical techniques to address a social science topic.
• Students from the social sciences looking to transition into research at the intersection of the social and computational sciences.
• Experienced data analysts and consultants with an interest in applying quantitative or computational approaches to social science research questions about or using machine learning.
• Students wishing to work in data analytics, business analytics, and other data-intensive roles that combine writing and interpretation with data analysis.

Learning outcomes

Upon completion of the MSc in Social Data Science will have:

• Developed an appreciation of how theories, methods, and practices from the social sciences and data science approaches to research can be mutually informative.
• Designed a research project that applies tools and methods from data science to address a social science research question.
• Compared and evaluated multiple computational approaches to a research question and chosen the most appropriate with due consideration to data access, computational resources, research ethics, and the state of academic knowledge.
• Communicated across disciplines and explained research outcomes in an accessible language and to a wide audience.
• Obtained a critical understanding of the uses and limitations of current computational approaches to social science questions.
• Manipulated and analysed large volumes of heterogeneous data or derived machine learning models by taking advantage of parallel, distributed, and other emerging computation methods.
• Selected and potentially extended or retrained machine learning models suitable for social science tasks in classification, interpretation, and explanation of social life.

How to Apply

All applications must be made through the University of Oxford Graduate Admissions site . There are two deadlines for the MSc Programme in November and January. Applications submitted for both deadlines are given equal consideration.

Please ensure that you start the online application process as early as you can, to ensure plenty of time to complete your application. Only applications that are complete by the deadline (including letters of reference) can be considered by the admissions team.

For MSc applicants interested in continuing on to doctoral study, please note that a separate application form to the combined MSc + DPhil (1+3) admissions route is no longer required. To be considered for MSc + DPhil (1+3) funding, applicants should apply to the MSc in Social Data Science only and submit an ESRC Grand Union Doctoral Training Partnership application as part of their other application materials.

This course can also be studied as a part of the Oxford 1+1 MBA programme . The Oxford 1+1 MBA programme is a unique, two-year graduate experience that combines the depth of a specialised, one-year master’s degree with the breadth of a top-ranking, one-year MBA.

The Oxford Internet Institute is participating in the University of Oxford’s pilot on selection procedures which aims to explore actions aimed at better contextualising admissions procedures for graduate students while minimising conscious and unconscious bias. For all our courses, the socio-economic data you provide in the application form will be used to contextualise the shortlisting and decision-making processes with a focus on providing opportunities for excellent students regardless of socioeconomic background. For details about the pilot and the actions we are taking, please see the University’s page on the Pilot selection procedure.

• Full-time: 10 months

Start date:

• October 2024

12 noon UK time (midday) on:

• Friday 10 November 2023
• Friday 5  January 2024

Dr Bernie Hogan

Associate Professor, Senior Research Fellow

Bernie is the Programme Director of the MSc course.

David Pepper

MSc Coordinator

David is the MSc Coordinator, and administrates the course.

Our induction programme is usually held in the first week of October, the week preceding the start of Michaelmas Term (also referred to as 0th week). During Induction Week students will be formally introduced to the  OII’s Director, Director of Graduate Studies, Programme Directors, Graduate Studies Support team, as well as our faculty and administrative team.  In addition students will be offered a full tour of the OII’s facilities and introduced to IT and library resources, followed by several informative MSc induction sessions. There is also ample opportunity to get to know fellow students and staff through student-led social activities and an afternoon drinks reception. 

Professional engagement

Over the course of the year the OII generally has a full schedule of lectures which students are welcome to attend, both in person and virtually. These range from formal departmental lectures, bespoke lectures from academic visitors, and Industry Insights lectures featuring discussions about life at a variety of technology-focused organisations, corporations, NGOs, and government departments.

Our MSc students are provided with working space in the department in both the dedicated MSc room at 1 St Giles and additional student working space at 41 St Giles. Students in the MSc program have access to departmental server provisions with both CPU and GPU capabilities as well as opportunities for access to Oxford’s high performance computing resources via Advanced Research Computing (ARC). All students are provided with Office365 and can request additional software provisions such as Overleaf, based on needs. The MSc room is adjacent to the OII’s library, specialising in social sciences, technology and computing. Students also have digital and physical access to the Bodleian Libraries, the University’s main research library.

Pastoral and Welfare Support

In addition to the pastoral support provided your college, as a department the OII seeks to support students by various means. Each degree programme has dedicated administrative support and the administrators in question will be able to help and advise students on a range of matters relating to their studies, or point them towards dedicated sources of support elsewhere in the University. Supervisors and the Director of Graduate Studies can also serve as a source of support, in addition to our dedicated disability lead and several Harassment Officers who can assist with connecting students with the appropriate support.

Social Data Science students take five compulsory foundation courses, three compulsory intensive courses, and two options courses, in addition to their thesis.

Please note that the course offering listed below is provisional, and may be subject to change.

Foundation courses

Social Data Science students take five compulsory foundation courses, designed to provide students with core skills, methods, theories and concepts required to undertake the remainder of the degree. These include laboratory and practical exercises to ensure that students are competent with particular techniques and able to use statistical and other software packages.

Applied Analytical Statistics

Applied analytical statistics is a course focusing on the tools and techniques used by social scientists to understand, describe and analyse (quantitative) data.

Foundations of Social Data Science

This course will introduce to some of the fundamental questions that have been raised in this domain across the social sciences.

Frontiers of Social Data Science

In this course, we take a look into the future, and focus on the emerging role of data by looking at specific contexts and issues.

Research Design for Social Data Science

This course introduces students to conceptual and methodological aspects of social science research methods, including both quantitative and qualitative methods.

Thesis Seminar

This is a capstone course for students in their final term. It is an opportunity for the whole cohort to reconvene and present their thesis work in progress to the group. Additionally, seminars may include advice on best practices in research and life after the MSc.

Intensive courses

The data science intensive is a series of three course modules taught one after the other in Michaelmas term. The first course, Fundamentals of Social Data Science, is a primer on data science fundamentals in Python, with an emphasis on wrangling, API access, and exploratory data analysis. The second course, Data Analytics at Scale, introduces concepts for efficiency, computability, scalability, and using data on the server. The third course, Introduction to Machine Learning, introduces the basics of classification, neural networks, and various approaches to supervision and learning.

These courses are assessed by a single take home exam which runs from exploratory data analysis to simple predictive models.

Fundamentals of Social Data Science in Python

This course is a four week intensive primer to get people up to speed on programming in the Python programming language for use with data science. It covers basics of claim-making, analysis, and Python for data science.

Data Analytics at Scale

The course will teach computational complexity and how to profile and increase the computational efficiency of Python code. It will also cover parallel and distributed computing approaches, and discuss data storage and retrieval techniques.

Machine Learning

This course covers the fundamentals of both supervised and unsupervised learning.

Option courses

Each student will select two option courses. The following list is representative, but may be updated.

Applied Machine Learning

This course teaches practical and applied Machine Learning techniques, focusing on how to apply the mathematical foundations of machine learning to domains where we are uncertain about the right answer or best approach, with an emphasis on temporal and graph-based approaches.

Digital Era Government and Politics

This option course will approach the study of government and politics through the lens of data science.

Fairness, Accountability, and Transparency in Machine Learning

Integrating historical and cultural context with contemporary scholarship, this course equips students with the technical and conceptual tools to engage critically with machine learning research and practice.

Internet Economics

A general introduction to the economics of the Internet, and to economics as a tool for social research more generally, emphasising issues such as competition, asymmetric information, trust and privacy, auctions, and network economics.

Introduction to Natural Language Processing for the Social Sciences

This course will develop conceptual and technical tools for large-scale analysis of linguistic data such as document collections, transcripts, and blogs.

Social Network Analysis and Interpretation

An introduction to the analysis of online social networks, providing students with the tools necessary to undertake research on online networks, and to give an overview of the type of questions that these data can answer.

Data-driven Network Science

Data-driven Network Science will introduce the students to network summaries and network models. Then different methods for analysing network data will be presented; these include likelihood-based methods as well as nonparametric methods.

A thesis of approximately 10,000 words (with a maximum of 15,000 words) is the capstone to the MSc experience. It provides students with the opportunity to apply the methods and approaches they have covered in the other parts of the course and carry out a substantive piece of academic research on a specialist topic of their choosing.

Academics within the Social Data Science programme will put forward both specific projects as well as general themes in which they would be happy to supervise theses. Students are also encouraged to propose projects of their own. Students will not be required to choose thesis topics until the second term in order to give them ample time for their research interests to develop and the opportunity to discuss topics with relevant faculty members.

Selected Past Alumni Theses

• Sarah Ball (2022) Triple standard in venture financing? The impact of an entrepreneur’s gender on investment decisions in equity crowdfunding
• Conrad Borchers (2022) Stack Overflow Correlation Networks Predict Technology Evolution and Labor Market Relevance
• Matt Chapman (2022) A recipe for gentrification: Predicting urban change with Tripadvisor data and machine learning.A
• Hannah Kirk (2021) Hatemoji – The Construction and Classification of Emoji-based Hate Speech
• Sven Giegerich (2021) Momentum Gains Attention – Enhancing Deep Time Series Momentum Strategies Using Attention-Based Networks
• Clare Brennan (2021) The impact of Ofsted reports on demand for state-funded primary schools in England, from 2012-2016
• Cameron Raymond (2021) Managing Online Rumour Proportions During Offline Protests
• Zo Ahmed (2020) Tackling Racial Bias in Automated Online Hate Detection
• Lisa Oswald (2020) Should we talk to climate skeptics
• Marcel Schliebs (2020) Understanding Social Distribution Networks of Chinese State-Backed Media
• Carla Intal (2019) Dissent and Rebellion in British Parliament

Students are assigned a general supervisor in the first term of their studies. The general supervisor can answer general questions and help the student navigate the department. In the second term students are then assigned a thesis supervisor with more direct topical or research experience for the student’s chosen thesis project. The department provides resources to help students discover faculty and propose a suitable thesis supervisor.

General supervision is provided by faculty from the Oxford Internet Institute. Thesis supervision can additionally span multiple departments, often with co-supervision within the OII. The following faculty members are eligible to supervise MSc Social Data Science students:

Dr Adam Mahdi

Dr Ana Valdivia

Professor Andrew Przybylski

Professor Brent Mittelstadt

Professor Carl-Benedikt Frey

Professor Chris Russell

Professor Ekaterina Hertog

Dr Fabian Braesemann

Dr Fabian Stephany

Dr Gemma Newlands

Professor Gesine Reinert

Dr Grant Blank

Professor Greg Taylor

Professor Helen Margetts

Professor Janet Pierrehumbert

Dr Joss Wright

Professor Kathryn Eccles

Dr Keegan McBride

Dr Luc Rocher

Professor Mark Graham

Professor Min Chen

Professor Philip Howard

Professor Ralph Schroeder

Professor Rebecca Eynon

Professor Renaud Lambiotte

Professor Mariarosaria Taddeo

Professor Sandra Wachter

Dr Scott A. Hale

Dr Varun Kanade

Professor Victoria Nash

Professor Viktor Mayer-Schönberger

Professor Vili Lehdonvirta

Dr Xiaowen Dong

Details of fees, living expenses, and definitions of home and overseas students, together with information about potential sources of funding are available from the  University’s Fees and Funding  website.

There are a number of sources of funding for postgraduate students at Oxford. Details of all scholarships for which candidates may be eligible can be found on the  University’s Fees and Funding  website.  The scholarships are all highly competitive and are awarded on academic merit.

Clarendon Scholarships

Clarendon is one of the biggest of the University’s scholarship schemes, offering around 170 new scholarships each year to academically outstanding graduates. Clarendon scholarships are competitive, prestigious and highly sought-after. As well as providing for fees and living costs Clarendon aims to enhance the Oxford experience by offering students the chance to form lasting social, academic and professional networks. Students can apply by completing the funding sections of the graduate admissions form. As part of the admissions process, the Oxford Internet Institute Scholarship Committee will decide which applicants to nominate to the University for consideration. Further details of this scholarship can be found on the University’s Clarendon Scholarships  page.

ESRC Grand Union Doctoral Training Partnership

The Grand Union DTP ESRC studentship is for MSc applicants who wish to continue on to doctoral study at the OII, or for applicants to the DPhil programme only.

The ESRC is the UK’s largest organisation for funding research on social and economic issues. The University, in collaboration with Brunel University and the Open University, hosts the Grand Union Doctoral Training Partnership – one of fourteen Doctoral Training Partnerships accredited by the ESRC as part of a Doctoral Training Network.

The Oxford Internet Institute’s graduate degree programmes are a recognised doctoral training pathway in the partnership and our Digital Social Science pathway is provided through two routes, Masters-to-DPhil (known as 1+3) and DPhil-only (known as +3), and is available to students studying part-time as well as those studying full-time.

In order to be considered for 1+3 funding via the Grand Union DTP ESRC studentship, you must apply to an OII MSc programme and select ‘ESRC Grand Union DTP Studentships in Social Sciences’ in the University of Oxford scholarships section of the University’s graduate application form. You must also complete a Grand Union DTP Application Form and upload it, together with your graduate application form, to be considered for nomination for the studentship.

Information about ESRC studentships at Oxford can be found on the Grand Union DTP website . Please ensure you have read all of the guidance available on the website before completing the Grand Union DTP Application Form. Questions can be directed to the Grand Union DTP Office .

ESRC studentships are open to both Home (UK) and International candidates, read more about the eligibility criteria here .

Black Academic Futures  

The Black Academic Futures Scholarships offer up to 30 scholarships for UK Black and Mixed-Black students to pursue graduate study at Oxford. Applicants need to apply to an Oxford department by the January programme deadline to be considered for the scholarship and ensure they include the ethnicity information in their application.  

Rhodes and Marshall Scholars

The OII welcomes a number of  Rhodes  and  Marshall Scholars  onto the MSc programme every year. Eligible students should apply for those scholarships before applying for a place on the MSc programme.

Refugee Academic Futures  

The Refugee Academic Futures scheme offers financial support to pursue graduate study at Oxford to students who are refugees or other people with lived experience of displacement. Applicants need to apply to an Oxford department by the January programme deadline to be considered for the scholarship.

Care-Experienced Academic Futures

The Care-Experienced Academic Futures scholarships offer financial support to students who have experienced being in care in the UK to pursue graduate study at Oxford.

Weidenfeld-Hoffmann Scholarships and Leadership Programme  

The Weidenfeld-Hoffmann Scholarships and Leadership Programme provides the opportunity to pursue fully-funded graduate studies at the University of Oxford, combined with a comprehensive programme of leadership development, long-term mentoring and networking.   

To be considered for this scholarship, you must select the Weidenfeld-Hoffmann Scholarships and Leadership Programme in the University of Oxford Scholarships section of the University’s graduate application form and submit your application for graduate study by the January deadline for your course.     

OII Shirley Scholarship

The OII awards a limited number of MSc Scholarships each academic year. These scholarships are open to students (from any country) and all applicants who are offered a place on our programme are automatically considered for an award. Scholarships are awarded on the basis of merit.

Recipients of an OII departmental scholarship will be designated as Shirley Scholars, and they will be supported by the  Shirley Scholars Fund  established in honour of OII founder donor Dame Stephanie Shirley.

MSc Social Data Science – Graduate Handbook

Download the handbook for study in the academic year 2023-2024

You can find general FAQs about applying to our courses, studying at the OII, and choosing a college on the study FAQs page .

How does the MSc in Social Data Science differ from the MSc in the Social Science of the Internet?

The MSc in Social Data Science is designed for students with core quantitative skills who wish to develop their skills for analysing structured and unstructured data using advanced computational techniques such as machine learning. Theses in Social Data Science might develop new computational approaches for analysing human behavioural data and/or apply such approaches to answer a social science question. The MSc in Social Science of the Internet is designed for students interested in research about the Internet and related technologies and their societal implications. Theses in this programme might include quantitative, qualitative, computational or mixed methods applied to a broad range of questions about digital phenomena and could address questions about technology policy or practice.

Should I apply for the MSc or the DPhil in Social Data Science?

A substantial amount of training in our programmes happens at the MSc level. It is therefore expected that applicants to DPhil programmes already hold a taught masters or other advanced degree. For Social Data Science, applicants should examine the MSc Social Data Science courses and are advised to apply for the MSc if their current experience covers less than half of the content taught within the MSc Social Data Science programme. DPhil students will work with their supervisors and the course director to identify any further areas of specialised training that is needed for their theses and opportunities to meet these needs from across the University. DPhil students will usually take the Foundation courses from the MSc Social Data Science unless they already have equivalent training.

Which application deadline should I apply for?

There are two deadlines for the MSc Programme. Applications submitted for both deadlines are given equal consideration, so please choose the deadline that works best for you. Please ensure that you start the online application process as early as you can, to ensure plenty of time to complete your application. Only applications that are complete by the deadline can be considered by the admissions team. All applications must be made through the  University of Oxford Graduate Admissions  site.

If I need to submit English Language Test results, when are they due?

You can read more about the English language requirements for graduate study applications in the graduate application guide.   This course requires proficiency in English at the University’s higher level . If you already have English language test scores at the required level achieved within two years of the start of the course to which you are applying, please include them in your application. However, you are not required to provide test scores when you submit your application.  

How do I choose a supervisor?

Our students are supervised by  OII faculty members and colleagues in partner departments.

Students will be assigned a supervisor in their first term based on their research interests. The supervisor will remain the main point of contact for keeping an eye on academic progress, and will liaise with the student and with other faculty members with whom the student is working with on their thesis.

What fees do I have to pay?

Course fees cover your teaching, and other academic services and facilities provided to support your studies. They do not cover your accommodation or other living costs.

See the University’s  guidance on fee status  and fee liability for information on  Home/Republic of Ireland ,  Islands  and  Overseas  student classification. As well as covering University and College fees, students will also have to support their maintenance costs. As Oxford is a relatively expensive place to live, it is recommended that students consult the University’s  guidance on living costs  when planning their budget, to cover accommodation, meals and other living expenses.

Do I have to live in Oxford during my studies?

Full-time students are required by the University’s regulations to be in residence in Oxford for each of the 8 weeks of Michaelmas and Trinity terms and the 10 weeks of Hilary term. You will be free to leave Oxford after the end of each term but are advised to return during the week prior to the start of the next term (referred to as 0th week).

Do you offer any online or part-time courses?

We do not currently offer any of our MSc or DPhil programmes online, and the MSc in Social Data Science is only offered in a full-time mode due to the intensive nature of several of the core courses. The DPhil in Social Data Science is offered in both full-time and part-time modes, and our MSc in  Social Science of the Internet  is offered part-time.

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Your Programmes

University of Oxford

DPhil MSc (PhD) Social Data Science

1 in 8 applicants to this programme received an offer.

Data shown above is for entry in academic year 2019/20 (sources) .

Previous Years

Why are there inexact numbers? For data protection reasons, when the number of applications, offers, or admissions is low for a given course (or in some cases, regardless of the numbers), some universities report only approximate numbers. Based on these, we have computed the range of possible values.

Data source

• FOI Request by Albert Warren. December 2019.

The acceptance rate , or offer rate, represents the fraction of applicants who received an offer. Note that this will be generally lower the acceptances rates (acceptances divided by applicants) published by many other sources. This article explains it in more detail. The acceptances generally indicate the number of offer holders who accepted the offer and fulfilled its conditions. For some universities, however, it denotes the number of applicants who accepted the offer, regardless of whether they subsequently met its conditions.

Data Reliability

Unless otherwise noted, the data presented comes from the universities and is generally reliable. However, some of the differences between years and/or courses may be due to different counting methodologies or data gathering errors. This may especially be the case if there is a sharp difference from year to year. If the data does not look right, click the "Report" button located near the top of the page.

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DPhil in Information, Communication and the Social Sciences

• Entry requirements
• Funding and Costs

College preference

• How to Apply

About the course

The DPhil (doctoral) course in Information, Communication and the Social Sciences provides an opportunity for highly-qualified students to undertake innovative Internet-related research.

The Oxford Internet Institute's (OII) students work on multidisciplinary research across the social sciences. Many projects fit within the following broad themes:

• digital knowledge and culture
• digital politics and government
• education, wellbeing and digital life
• ethics and philosophy of information
• information geography and inequality
• digital policy and online security
• economics of information and the internet
• online platforms and social networks.

Over this three- to four-year course (six to eight years for the part-time course), students produce an important and original piece of scholarship that will make a significant contribution to the dynamic area of internet research. OII DPhil graduates have the qualities and transferable skills necessary to excel in teaching, research, policymaking or business.

Doctoral students at the OII address research questions from across a spectrum of disciplines. OII DPhil students anchor their research in disciplinary questions (in, for instance, politics or sociology), while also situating their research in broader social science theories and methods.  OII faculty are international leaders in their research fields, and their teaching and supervision reflect their innovative research. The diverse cohorts of doctoral students complement the strength of the course by providing a multidisciplinary peer network for students to engage in ideas, discussion and debate.

The DPhil course at the OII is also available on a part-time basis. The part-time course is spread over six to eight years of study and research. The part-time degree offers the flexibility of part-time study with the same high standards and requirements as the full-time DPhil course. The part-time DPhil also provides an excellent opportunity for professionals in high tech industries to undertake rigorous long-term research that may be relevant to their working life. Please visit the department website for further details on part-time doctoral study  or contact the Graduate Studies Assistant .

As a part-time student you will be required to attend seminars, supervision meetings and other obligations in Oxford for a minimum of 30 days each year. Attendance will be required during term-time a minimum of one day each week. There will be limited flexibility in the dates and pattern of attendance, which will normally be determined by the fixed teaching and seminar schedule during term. Attendance may be required outside of term-time on dates to be determined by mutual agreement with your supervisor. You will have the opportunity to tailor your part-time study in liaison with your supervisor and agree your pattern of attendance.

Supervision

The allocation of graduate supervision for this course is the responsibility of the Oxford Internet Institute and it is not always possible to accommodate the preferences of incoming graduate students to work with a particular member of staff. Please see the full list of faculty members eligible to supervise DPhil students for this course. Under exceptional circumstances a supervisor may be found outside the Oxford Internet Institute. A supervisor may be found outside the list on the course web page, and co-supervision is also possible.

Students should normally expect to meet with their supervisor around three to four times a term.

The sequence of milestones for a DPhil student are as follows:

• Admission as a Probationer Research Student (PRS)
• Transfer to DPhil status (‘Transfer of Status’)
• Confirmation of DPhil status for DPhil students (‘Confirmation of Status’)
• Submission of thesis

All students will be initially admitted to the status of Probationer Research Student (PRS), during which time you will be required to attend and pass core modules from the OII’s training programme as directed by the Graduate Studies Committee. Students who have already completed similar courses in their past academic career can request an exemption from one or more modules by providing sufficient evidence. 

Within a maximum of four terms as a full-time PRS student or eight terms as a part-time PRS student, you will be expected to apply for, and achieve, transfer of status from Probationer Research Student to DPhil status. A successful transfer of status will require the student to show that their proposed thesis and treatment represents a viable topic and that their written work and interview show that they have a good knowledge and understanding of the subject. Students are also required to demonstrate satisfactory completion of the core modules by this point.

Following successful transfer, students will need to apply for and gain confirmation of DPhil status to show that the work continues to be on track. This will need to be completed within nine terms of admission for full-time students and eighteen terms of admission for part- time students.

Both milestones involve an interview with two assessors (other than your supervisor) and therefore provide important experience for the final oral examination.

Full-time students will be expected to submit an original thesis of not more than 100,000 words three or, at most, four years from the date of admission. If you are studying part-time, you be required to submit your thesis after six or, at most, eight years from the date of admission. To be successfully awarded a DPhil In Information, Communication and the Social Sciences you will need to defend your thesis orally (viva voce) in front of two appointed examiners.

Graduate destinations

The Oxford Internet Institute provides you with skills and opportunities in teaching, research, policymaking and business innovation. Employers recognise the value of a degree from the University of Oxford, and the OII's doctoral students regularly go on to secure excellent positions in academia, industry, government, and NGOs.

Alumni who have pursued academic careers have taken up research and teaching positions at the University of Oxford, Cornell University, University of Hong Kong, Imperial College London, Durham University, University of New South Wales, Coventry University, University of Leicester, University of Ottawa, and Michigan State University. OII DPhil alumni also work in wide-range of organizations including The World Bank, Open Technology Fund, Oxfam, Cisco, McKinsey and Google.

The  OII Alumni page  features interviews from both MSc and DPhil alumni about their time at the Department and career paths after Oxford.

Changes to this course and your supervision

The University will seek to deliver this course in accordance with the description set out in this course page. However, there may be situations in which it is desirable or necessary for the University to make changes in course provision, either before or after registration. The safety of students, staff and visitors is paramount and major changes to delivery or services may have to be made in circumstances of a pandemic, epidemic or local health emergency. In addition, in certain circumstances, for example due to visa difficulties or because the health needs of students cannot be met, it may be necessary to make adjustments to course requirements for international study.

Where possible your academic supervisor will not change for the duration of your course. However, it may be necessary to assign a new academic supervisor during the course of study or before registration for reasons which might include illness, sabbatical leave, parental leave or change in employment.

For further information please see our page on changes to courses and the provisions of the student contract regarding changes to courses.

Entry requirements for entry in 2024-25

Proven and potential academic excellence.

The requirements described below are specific to this course and apply only in the year of entry that is shown. You can use our interactive tool to help you  evaluate whether your application is likely to be competitive .

Please be aware that any studentships that are linked to this course may have different or additional requirements and you should read any studentship information carefully before applying. 

Degree-level qualifications

As a minimum, applicants should hold or be predicted to achieve the following UK qualifications or their equivalent:

• a master's degree with a mark of at least 67% ;  and
• a first-class or strong upper second-class undergraduate degree with honours in any subject.

It is expected that applicants will hold a taught master's or other advanced degree, normally in one of the social sciences, including law, but candidates from other disciplines embracing the social study of technology will also be considered.

For applicants with a degree from the USA, the minimum GPA sought is 3.5 out of 4.0.

If your degree is not from the UK or another country specified above, visit our International Qualifications page for guidance on the qualifications and grades that would usually be considered to meet the University’s minimum entry requirements.

GRE General Test scores

No Graduate Record Examination (GRE) or GMAT scores are sought.

Other qualifications, evidence of excellence and relevant experience

• Strong analytical abilities in understanding the social aspects of the internet, World Wide Web and related technologies, as shown by the candidate’s writing sample and/or the reports of referees, is required.
• Part-time applicants will also be expected to show evidence of the ability to commit time to study and, if applicable, an employer's commitment to make time available to study, to complete coursework, and attend course and University events and modules. Where appropriate, evidence should also be provided of permission to use employers’ data in the proposed research project.
• While prior publication is not required, evidence of successful academic publication will be taken into account and may provide the applicant with an advantage.
• It would be expected that graduate applicants would be familiar with the recent published work of their proposed supervisor.

English language proficiency

This course requires proficiency in English at the University's  higher level . If your first language is not English, you may need to provide evidence that you meet this requirement. The minimum scores required to meet the University's higher level are detailed in the table below.

*Previously known as the Cambridge Certificate of Advanced English or Cambridge English: Advanced (CAE) † Previously known as the Cambridge Certificate of Proficiency in English or Cambridge English: Proficiency (CPE)

Your test must have been taken no more than two years before the start date of your course. Our Application Guide provides  further information about the English language test requirement .

Declaring extenuating circumstances

If your ability to meet the entry requirements has been affected by the COVID-19 pandemic (eg you were awarded an unclassified/ungraded degree) or any other exceptional personal circumstance (eg other illness or bereavement), please refer to the guidance on extenuating circumstances in the Application Guide for information about how to declare this so that your application can be considered appropriately.

You will need to register three referees who can give an informed view of your academic ability and suitability for the course. The  How to apply  section of this page provides details of the types of reference that are required in support of your application for this course and how these will be assessed.

Supporting documents

You will be required to supply supporting documents with your application. The  How to apply  section of this page provides details of the supporting documents that are required as part of your application for this course and how these will be assessed.

Performance at interview

Interviews are normally held as part of the admissions process.

All applications are reviewed by at least two members of faculty with relevant experience and expertise. Applicants are shortlisted based on the quality of  written application. Those who are shortlisted will normally be interviewed.

Interviews are usually held around three to six weeks after the application deadline. There is usually only one interview held, which lasts 30 to 40 minutes and can be held via video conferencing software. You will be asked questions about your academic background, your research plan, and why you think the Oxford Internet Institute would be the best place to conduct your studies. The interview panel will consist of at least two interviewers which will normally include the potential supervisor.

How your application is assessed

Your application will be assessed purely on your proven and potential academic excellence and other entry requirements described under that heading.

References  and  supporting documents  submitted as part of your application, and your performance at interview (if interviews are held) will be considered as part of the assessment process. Whether or not you have secured funding will not be taken into consideration when your application is assessed.

An overview of the shortlisting and selection process is provided below. Our ' After you apply ' pages provide  more information about how applications are assessed . 

Shortlisting and selection

Students are considered for shortlisting and selected for admission without regard to age, disability, gender reassignment, marital or civil partnership status, pregnancy and maternity, race (including colour, nationality and ethnic or national origins), religion or belief (including lack of belief), sex, sexual orientation, as well as other relevant circumstances including parental or caring responsibilities or social background. However, please note the following:

• socio-economic information may be taken into account in the selection of applicants and award of scholarships for courses that are part of  the University’s pilot selection procedure  and for  scholarships aimed at under-represented groups ;
• country of ordinary residence may be taken into account in the awarding of certain scholarships; and
• protected characteristics may be taken into account during shortlisting for interview or the award of scholarships where the University has approved a positive action case under the Equality Act 2010.

Initiatives to improve access to graduate study

This course is taking part in a continuing pilot programme to improve the selection procedure for graduate applications, in order to ensure that all candidates are evaluated fairly.

For this course, socio-economic data (where it has been provided in the application form) will be used to contextualise applications at the different stages of the selection process.  Further information about how we use your socio-economic data  can be found in our page about initiatives to improve access to graduate study.

Processing your data for shortlisting and selection

Information about  processing special category data for the purposes of positive action  and  using your data to assess your eligibility for funding , can be found in our Postgraduate Applicant Privacy Policy.

Admissions panels and assessors

All recommendations to admit a student involve the judgement of at least two members of the academic staff with relevant experience and expertise, and must also be approved by the Director of Graduate Studies or Admissions Committee (or equivalent within the department).

Admissions panels or committees will always include at least one member of academic staff who has undertaken appropriate training.

Other factors governing whether places can be offered

The following factors will also govern whether candidates can be offered places:

• the ability of the University to provide the appropriate supervision for your studies, as outlined under the 'Supervision' heading in the  About  section of this page;
• the ability of the University to provide appropriate support for your studies (eg through the provision of facilities, resources, teaching and/or research opportunities); and
• minimum and maximum limits to the numbers of students who may be admitted to the University's taught and research programmes.

Offer conditions for successful applications

If you receive an offer of a place at Oxford, your offer will outline any conditions that you need to satisfy and any actions you need to take, together with any associated deadlines. These may include academic conditions, such as achieving a specific final grade in your current degree course. These conditions will usually depend on your individual academic circumstances and may vary between applicants. Our ' After you apply ' pages provide more information about offers and conditions . 

In addition to any academic conditions which are set, you will also be required to meet the following requirements:

Financial Declaration

If you are offered a place, you will be required to complete a  Financial Declaration  in order to meet your financial condition of admission.

Disclosure of criminal convictions

In accordance with the University’s obligations towards students and staff, we will ask you to declare any  relevant, unspent criminal convictions  before you can take up a place at Oxford.

Academic Technology Approval Scheme (ATAS)

Some postgraduate research students in science, engineering and technology subjects will need an Academic Technology Approval Scheme (ATAS) certificate prior to applying for a  Student visa (under the Student Route) . For some courses, the requirement to apply for an ATAS certificate may depend on your research area.

The department prides itself on providing a stimulating and supportive environment in which all students can flourish. The OII faculty works at the cutting-edge of their fields, and this innovative research is fully reflected in their course teaching. As a fully multidisciplinary department, the OII offers you the opportunity to study academic, practical and policy-related issues that can only be understood by drawing on contributions from across many different fields.

In addition to the formal requirements of the DPhil thesis, all OII doctoral students have access to regular training in the key professional skills necessary to support their research and future employment. These range from classes on advanced research methods as part of the OII’s option course offerings to professional development training (provided both by the department and the University) such as presentation skills, academic writing and navigating the process of peer review.

You will attend a weekly seminar in which you will present your own work for critique, and critique the work of your peers. The OII also provides opportunities for DPhil students to gain teaching experience through mentored assistantship roles in some of its core MSc courses.

The department's busy calendar of seminars and events brings many of the most important people in internet research, innovation and policy to the OII, allowing students to engage with cutting-edge scholarship and debates around the internet and digital technologies.

OII students also take full advantage of the substantial resources available at the University of Oxford, including world-leading research facilities and libraries, and a buzzing student scene. The departmental library provides students access to a range of resources. Additionally, the  Social Sciences Library provides valuable additional resources of which many students choose to take advantage of.

Oxford Internet Institute

The Oxford Internet Institute (OII) is a dynamic and innovative department for research and teaching relating to the internet, located in a world-leading traditional research university. The multidisciplinary OII offers the opportunity to study academic, practical and policy-related issues that can only be understood by drawing on contributions from many different fields.

The OII is the only major department in a top-ranked international university to offer multidisciplinary courses in the social sciences dedicated to understanding the impact of the internet, data, and information technologies on society. We offer masters and doctoral level education across several degrees focused on social data science or the social science of the internet and technology.

Digital connections are now embedded in almost every aspect of our daily lives, and research on individual and collective behaviour online is crucial to understanding our social, economic and political world. As a fully multi-disciplinary department, we offer our students the opportunity to study academic, practical and policy-related issues and pursue cutting-edge research into the societal implications of the internet and digital technologies.

Our academic faculty and graduate students are drawn from many different disciplines: we believe this combined approach is essential to tackle society’s big questions. Together, we aim to positively shape the development of our digital world for the public good.

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The University expects to be able to offer over 1,000 full or partial graduate scholarships across the collegiate University in 2024-25. You will be automatically considered for the majority of Oxford scholarships , if you fulfil the eligibility criteria and submit your graduate application by the relevant December or January deadline. Most scholarships are awarded on the basis of academic merit and/or potential. 

For further details about searching for funding as a graduate student visit our dedicated Funding pages, which contain information about how to apply for Oxford scholarships requiring an additional application, details of external funding, loan schemes and other funding sources.

Please ensure that you visit individual college websites for details of any college-specific funding opportunities using the links provided on our college pages or below:

Please note that not all the colleges listed above may accept students on this course. For details of those which do, please refer to the College preference section of this page.

Further information about funding opportunities for this course can be found on the institute's website.

Annual fees for entry in 2024-25

Full-time study.

Further details about fee status eligibility can be found on the fee status webpage.

Part-time study

Information about course fees.

Course fees are payable each year, for the duration of your fee liability (your fee liability is the length of time for which you are required to pay course fees). For courses lasting longer than one year, please be aware that fees will usually increase annually. For details, please see our guidance on changes to fees and charges .

Course fees cover your teaching as well as other academic services and facilities provided to support your studies. Unless specified in the additional information section below, course fees do not cover your accommodation, residential costs or other living costs. They also don’t cover any additional costs and charges that are outlined in the additional information below.

Continuation charges

Following the period of fee liability , you may also be required to pay a University continuation charge and a college continuation charge. The University and college continuation charges are shown on the Continuation charges page.

Where can I find further information about fees?

The Fees and Funding  section of this website provides further information about course fees , including information about fee status and eligibility  and your length of fee liability .

Additional information

There are no compulsory elements of this course that entail additional costs beyond fees (or, after fee liability ends, continuation charges) and living costs. However, please note that, depending on your choice of research topic and the research required to complete it, you may incur additional expenses, such as travel expenses, research expenses, and field trips. You will need to meet these additional costs, although you may be able to apply for small grants from your department and/or college to help you cover some of these expenses.

Please note that you are required to attend in Oxford for a minimum of 30 days each year, and you may incur additional travel and accommodation expenses for this. Also, depending on your choice of research topic and the research required to complete it, you may incur further additional expenses, such as travel expenses, research expenses, and field trips. You will need to meet these additional costs, although you may be able to apply for small grants from your department and/or college to help you cover some of these expenses.

Whilst many graduate students do undertake employment to support their studies, please remember that students on the full-time arrangement of the OII's DPhil course are subject to limits on the number of hours that may be worked each week. Part-time student are not subject to these limitations.

Within these limitations, many of the OII's existing full-time DPhil students have been employed on a short or long-term basis as Research Assistants on grant-funded projects gaining valuable research experience. The OII also offers Teaching Assistant positions on the MSc degree for DPhil students who can display the appropriate skills. In addition, there are employment opportunities within the University (such as teaching, translation, and research assistance) as well as within the OII.

For full information on employment whilst on course, please see the University's  paid work guidelines for Oxford graduate students .

Living costs

In addition to your course fees, you will need to ensure that you have adequate funds to support your living costs for the duration of your course.

For the 2024-25 academic year, the range of likely living costs for full-time study is between c. £1,345 and £1,955 for each month spent in Oxford. Full information, including a breakdown of likely living costs in Oxford for items such as food, accommodation and study costs, is available on our living costs page. The current economic climate and high national rate of inflation make it very hard to estimate potential changes to the cost of living over the next few years. When planning your finances for any future years of study in Oxford beyond 2024-25, it is suggested that you allow for potential increases in living expenses of around 5% each year – although this rate may vary depending on the national economic situation. UK inflationary increases will be kept under review and this page updated.

If you are studying part-time your living costs may vary depending on your personal circumstances but you must still ensure that you will have sufficient funding to meet these costs for the duration of your course.

Students enrolled on this course will belong to both a department/faculty and a college. Please note that ‘college’ and ‘colleges’ refers to all 43 of the University’s colleges, including those designated as societies and permanent private halls (PPHs). 

If you apply for a place on this course you will have the option to express a preference for one of the colleges listed below, or you can ask us to find a college for you. Before deciding, we suggest that you read our brief  introduction to the college system at Oxford  and our  advice about expressing a college preference . For some courses, the department may have provided some additional advice below to help you decide.

The following colleges accept students for full-time study on this course:

• Balliol College
• Blackfriars
• Campion Hall
• Christ Church
• Exeter College
• Green Templeton College
• Hertford College
• Keble College
• Kellogg College
• Linacre College
• Mansfield College
• Pembroke College
• Reuben College
• St Antony's College
• St Catherine's College
• St Cross College
• St Edmund Hall
• Trinity College
• Wadham College
• Wolfson College
• Wycliffe Hall

The following colleges accept students for part-time study on this course:

Before you apply

Our  guide to getting started  provides general advice on how to prepare for and start your application. You can use our interactive tool to help you  evaluate whether your application is likely to be competitive .

If it's important for you to have your application considered under a particular deadline – eg under a December or January deadline in order to be considered for Oxford scholarships – we recommend that you aim to complete and submit your application at least two weeks in advance . Check the deadlines on this page and the  information about deadlines  in our Application Guide.

Application fee waivers

An application fee of £75 is payable per course application. Application fee waivers are available for the following applicants who meet the eligibility criteria:

• applicants from low-income countries;
• refugees and displaced persons; 
• UK applicants from low-income backgrounds; and 
• applicants who applied for our Graduate Access Programmes in the past two years and met the eligibility criteria.

You are encouraged to  check whether you're eligible for an application fee waiver  before you apply.

Readmission for current Oxford graduate taught students

If you're currently studying for an Oxford graduate taught course and apply to this course with no break in your studies, you may be eligible to apply to this course as a readmission applicant. The application fee will be waived for an eligible application of this type. Check whether you're eligible to apply for readmission .

Do I need to contact anyone before I apply?

You are recommended to contact a potential supervisor (or supervisors) in the first instance to get feedback on the fit of your proposed research with the expertise of the supervisor before you apply. The full list of faculty members eligible to supervise DPhil students for this course, including their research interests and contact details, can be found on the departmental website. Please note that the Oxford Internet Institute will only admit students where appropriate supervision is available.

Completing your application

You should refer to the information below when completing the application form, paying attention to the specific requirements for the supporting documents .

For this course, the application form will include questions that collect information that would usually be included in a CV/résumé. You should not upload a separate document. If a separate CV/résumé is uploaded, it will be removed from your application .

If any document does not meet the specification, including the stipulated word count, your application may be considered incomplete and not assessed by the academic department. Expand each section to show further details.

Proposed field and title of research project

Under the 'Field and title of research project' please enter your proposed field or area of research if this is known. If the department has advertised a specific research project that you would like to be considered for, please enter the project title here instead.

You should not use this field to type out a full research proposal. You will be able to upload your research supporting materials separately if they are required (as described below).

Proposed supervisor

If known, under 'Proposed supervisor name' enter the name of the academic(s) who you would like to supervise your research. Otherwise, leave this field blank.

Referees: Three overall, academic and/or professional

Whilst you must register three referees, the department may start the assessment of your application if two of the three references are submitted by the course deadline and your application is otherwise complete. Please note that you may still be required to ensure your third referee supplies a reference for consideration.

Professional references are acceptable, particularly if you have been out of education for some time, though these should focus particularly on your intellectual abilities rather than more narrowly on job performance.

Your references will support intellectual ability, academic achievement, aptitude and potential for research investigation.

Official transcript(s)

Your transcripts should give detailed information of the individual grades received in your university-level qualifications to date. You should only upload official documents issued by your institution and any transcript not in English should be accompanied by a certified translation.

More information about the transcript requirement is available in the Application Guide.

Personal statement and research proposal: Statement of up to a maximum of 500 words and proposal of up to a maximum of 2,500 words

Your statement of purpose/personal statement and research proposal should be submitted as a single, combined document with clear subheadings. Please ensure that the word counts for each section are clearly visible in the document.

Personal statement

You should submit a convincing personal statement (statement of purpose) explaining your reasons for applying to the course and highlighting your relevant academic and professional experience. It should be written in English and should be a maximum of 500 words.

If possible, please ensure that the word count is clearly displayed on the document.

Research proposal 

You should also submit a research proposal that should focus on your proposed research topic, rather than your personal achievements, interests and aspirations. Your proposal should include:

• an indicative bibliography;
• an indicative title;
• a short introduction/synopsis;
• a discussion of the most relevant scholarly literature; and
• a research question or hypothesis.

The issue or question should emerge from your review of the literature. Please also provide a rationale for the importance of this research topic.

Your research proposal should also indicate your proposed methodological approach. This will depend on the kind of research you envisage. If empirical research is planned, then please discuss the likely data or evidence to be collected. At this stage these ideas are exploratory, and likely to develop and change once you are accepted.

Your research proposal should be written in English and should be a maximum of 2,500 words. You do not need to include the indicative bibliography in your word count. 

Your research proposal will be assessed for your potential to carry out doctoral research, the quality and coherence of the proposal and the originality of the project.

It will be normal for your ideas to subsequently change in some ways as you develop your project. You should nevertheless make the best effort you can to demonstrate the extent of your research question, sources and method at this moment.

Written work: One essay of a maximum of 2,000 words

An academic essay or other writing sample from your most recent qualification, written in English, is required. An extract of the requisite length from longer work is also permissible.

The word count does not need to include any bibliography or brief footnotes.

If you have not previously written on areas closely related to the proposed research topic, you may provide written work on any topic that best demonstrates your academic abilities.

This will be assessed for evidence that demonstrates your aptitude and potential for research investigation.

Start or continue your application

You can start or return to an application using the relevant link below. As you complete the form, please  refer to the requirements above  and  consult our Application Guide for advice . You'll find the answers to most common queries in our FAQs.

Application Guide   Apply - Full time Apply - Part time

ADMISSION STATUS

Closed to applications for entry in 2024-25

Register to be notified via email when the next application cycle opens (for entry in 2025-26)

12:00 midday UK time on:

Friday 5 January 2024 Latest deadline for most Oxford scholarships Final application deadline for entry in 2024-25

*Three-year average (applications for entry in 2021-22 to 2023-24)

Further information and enquiries

This course is offered by the Oxford Internet Institute

• Course page on the institute's website
• Funding information from the institute
• Academic and research staff
• Research at the institute
• Department open days
• Social Sciences Division
• Residence requirements for full-time courses
• Postgraduate applicant privacy policy

Course-related enquiries

Advice about contacting the department can be found in the How to apply section of this page

✉ [email protected] ☎ +44 (0)1865 287210

Application-process enquiries

See the application guide

Visa eligibility for part-time study

We are unable to sponsor student visas for part-time study on this course. Part-time students may be able to attend on a visitor visa for short blocks of time only (and leave after each visit) and will need to remain based outside the UK.