data science phd scholarship in uk

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Fully Funded PhDs in Data Science, AI and Machine Learning

The University of Liverpool’s Centre for Doctoral training in Distributed Algorithms (CDT) are currently looking for students to join their fully funded PhDs in Data Science, AI and Machine Learning.

The team aim to develop 60 PhD students to meet the world’s pressing need for highly-trained data scientists and work with industry and government to help solve real-world problems.

Applicants come from a range of subjects and backgrounds, including:

• Computer Science
• Department of Civil Engineering and Industrial Design
• Earth, Ocean and Ecological Sciences
• Electrical Engineering and Electronics
• Geography and Planning
• Mathematical Sciences
• Mechanical and Aerospace Engineering

The fully funded PhD studentships are open to home and international students. You’ll be working as part of a cohort in a collaborative environment alongside other PhD students, postdoc researchers and data scientists. Other benefits include:

•  PhD projects co-defined and co-supervised with a project partner
•  Monthly tax-free payment of £1,338.50
•  Annual research grant
•  Placements in year 3
•  Long-term employment potential
•  Inclusive and supportive cohort environment
•  Technical, professional and personal training and development
•  Access to state-of-the-art high-performance computers

Interested?

The team would love to hear from you. Please do get in touch to find out more.

Email Kelli or Sara ( [email protected] ) if you have any questions.

They will also be at the Careers Studio on Friday 22 July between 11am – 1pm – drop-in to speak to the team, no appointment necessary.

Click here to find out more and apply

Further reading

• Click here to discover what our current students are working on and who with.
• Email one of our Student Ambassadors here and arrange a call with them.
• View our applicant information and guidance.
• Simon Maskell, CDT Director Bio
• Student Featured 2
• Careers and Employability
• CDT in Distributed Algorithms.
• Centre for Doctoral Training in Distributed Algorithms

Department of Mathematics

PhD Scholarship in Network Data Science

A full PhD Scholarship is available in the area of statistical learning for network-structured data.

• Academic year: 2024/25
• Open to: UK (home) students
• Qualification level: Postgraduate research
• Number available: 1

There has been a recent explosion in the availability of network data, arising across a multitude of fields from biology and medicine to social media, cyber security and climate science. Your research will contribute to efficient modelling and forecasting of evolving, inter-connected stochastic processes by exploiting simultaneously collected information across network nodes and edges, and integrating their dynamic statistical properties. You will use the techniques you develop to maximise insight in scientific and industrial applications.

This exciting opportunity is aligned to the strategic EPSRC-funded research programme on Network Stochastic Processes and Time Series (NeST) which brings together researchers at the Universities of York, Oxford, Bath, Bristol, Imperial College London and the London School of Economics and Political Science, with industrial and government partners such as BT, EDF and the Office for National Statistics.

You will be working with Professor Marina Knight at the University of York node, be part of the growing NeST team and engage in collaboration between institutions.

Open to UK (home) students only.

Open to students in the Department of Mathematics.

Applications are invited from UK students who aim to commence their PhD studies during 2024. Applicants should hold, or be close to completing, an Honours undergraduate degree or a Masters degree in Statistics, or a closely related field.

You should be self-motivated, with a keen interest in developing methodological and computational statistical techniques in answer to practical problems, backed up by demonstrably strong mathematical/statistical and programming skills.

Application deadline: Monday 28 October 2024, 11.59pm GMT

Please send your CV with academic transcripts and a cover letter to Professor Marina Knight ( [email protected] ).

Contact details

[email protected] +44 (0)1904 323 097

DPhil in Social Data Science

• Entry requirements
• Funding and Costs

College preference

• How to Apply

About the course

The DPhil in Social Data Science is an advanced research degree which provides the opportunity to investigate and address novel research questions at the intersection of the computational and social sciences, supported by the multidisciplinary faculty at the OII, Mathematics, Computer Science, Engineering, Statistics,  and other departments across the University of Oxford. The DPhil, normally taking three to four years of full-time study to complete, is known as a PhD at other universities.

The DPhil in Social Data Science at the Oxford Internet Institute (OII) will introduce you to cutting-edge research whilst studying in a beautiful, historic setting that is both student- and family-friendly. During your study at Oxford, you are encouraged to pioneer new approaches to contemporary social and policy issues online, developing new computational and data-driven methodology to inform the development and governance of technology. As a student, you will be part of a diverse cohort of research students, of many nationalities and from a wide range of scientific backgrounds. Research students in Social Data Science are graduates in subjects from computer science and mathematics to physics, as well as transdisciplinary subjects such as human-centred data science and complex systems.

The course combines individual supervision with a selection of lectures, seminars, transferrable skills training, and opportunities to participate in leading-edge research activities. OII faculty are world class experts working in the cutting-edge of their fields, and this innovative research is fully reflected in their course teaching. You will be able to audit courses led by faculty at the OII, as well as courses in other departments.

The programme provides a strong computational foundation, training you to develop new research skills in areas such as machine learning, statistical modelling, large-scale data collection, algorithm auditing, or network science. The DPhil in Social Data Science provides you with a rare grounding in both technical skills and social science research , helping you build critical skills to study digital technologies. There are weekly opportunities for you to interact with DPhil in Information, Communication and the Social Sciences students, providing a rich multidisciplinary environment.

As a full-time student, you are expected to continue working outside of the University terms with an annual holiday of approximately eight weeks.

Part-time study

The DPhil programme at the OII is also available on a part-time basis. The part-time programme is spread over six to eight years of study and research. It offers the flexibility of part-time study with the same high standards and requirements as the full-time DPhil programme. The part-time DPhil also provides an excellent opportunity for professionals in industry and civil society to undertake rigorous long-term research that may be relevant to their career.

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.

Supervision for the DPhil in Social Data Science spans multiple departments (please see the full list of faculty members  eligible to supervise DPhil students for this programme). A supervisor may be found outside the list on the course web page, and co-supervision is also possible. All students will have at least one supervisor who is a faculty member of the OII.

Students should normally expect to meet with their supervisor at least three to four times a term. A more typical pattern is weekly or bimonthly, at least until you reach the stage of writing up your thesis.

The first year is a probationary year, soon after which, subject to satisfactory progress, you will be expected to transfer from Probationer Research Student (PRS) status to full DPhil status. The Transfer of Status takes place within a maximum of four terms for full-time students or eight terms for part-time students. A second formal assessment of progress, Confirmation of Status, takes place later in the programme, normally at the end of the third year. The Transfer of Status and Confirmation of Status assessments are conducted by two members of staff other than the student’s supervisor(s) or advisors.

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

Students initially admitted to the status of Probationer Research Student (PRS) are required to attend and pass core modules from the OII’s training programme. Students who have already completed similar courses in their past academic career should request an exemption from one or more modules by providing sufficient evidence.  

A successful transfer of status from PRS to DPhil status will require the student to show that their proposed thesis 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 foundational courses 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 18 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 Social Data Science 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 industry, government, and NGOs. 

Alumni who have pursued academic careers have taken up research and teaching positions including notably at the University of Oxford, Cornell University, University of Hong Kong, Imperial College London, and TU Delft. OII DPhil alumni have worked in a wide range of organisations 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 65% ; and
• a first-class or strong upper second-class undergraduate degree with honours  in any subject.

It is expected that all applicants will hold a taught masters or other advanced degree.

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, are required. It would be expected that graduate applicants would be familiar with the recent published work of their proposed supervisor.

Applicants are expected to demonstrate quantitative aptitude or experience in at least half of the material covered by the MSc in Social Data Science.

Applicants may demonstrate this aptitude/experience in a variety of ways including:

• graduate and undergraduate transcripts;
• on-the-job training and practical experience;
• evidence of the successful completion of online courses.

Applicants are not expected to have published academic work previously, although publication may help the assessors judge your writing ability and thus could help your application.

Academic research related to data science or experience working in related businesses is not required, but may be an advantage.

Part-time applicants will also be expected to demonstrate their ability to commit sufficient time to study and spend a minimum of 30 days in Oxford per year, including attendance of teaching, seminars and departmental events, to complete coursework, and attend course and University events and modules. If applicable, evidence should also be provided of the employer’s commitment to make time available for study, and of the student’s permission to use employers’ data in the proposed research project.

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 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 the written application. Those who are shortlisted will usually be interviewed.

Interviews are typically held 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 a video conferencing platform. 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 DPhil in Social Data Science is offered by the Oxford Internet Institute (OII) in partnership with Statistics, Engineering Science, Sociology, and other departments. The OII faculty works at the cutting-edge of their fields, and this innovative research is fully reflected in their course teaching. The department prides itself on providing a stimulating and supportive environment in which all students can flourish. 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 including the texts required for the degree. Other University libraries provide valuable additional resources of which many students choose to take advantage.

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.

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 programme that entail additional costs beyond fees 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 programme 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:

• Blackfriars
• Campion Hall
• Christ Church
• Exeter College
• Green Templeton College
• Hertford College
• Jesus College
• Keble College
• Kellogg College
• Linacre College
• Nuffield College
• Reuben College
• St Antony's College
• St Catherine's College
• St Cross College
• St Hilda's 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 and when to apply  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, but should focus particularly on your intellectual abilities rather than more narrowly on job performance.

Your references will be assessed for:

• your intellectual ability;
• your academic achievement; and 
• your motivation and interest in the course and subject area.

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 a maximum of 500 words and a proposal of 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

Your statement should explain your motivation for applying for the DPhil course at Oxford and the specific research areas that interest you and/or you intend to specialise in. It should focus on your academic achievements and research interests rather than personal achievements, interests and aspirations. You should also include details of any relevant experience in engaging in social data science related research.

Your statement should be written in English and be a maximum of 500 words.

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

Your statement will be assessed for:

• interest and commitment for the study of social data science;
• evidence of aptitude for working with data-driven research; and
• alignment of your areas of interest with the availability of supervision, as all students will be assigned a supervisor to guide their research.

Research proposal

A coherent thesis proposal is required in an area of study covered by at least one member of the research staff within the Social Data Science programme. Your proposal should focus on specific research you propose to undertake rather than personal achievements, interests and aspirations.

The proposal should be submitted in English only and be a maximum of 2,500 words. The word count does not need to include any bibliography or brief footnotes.

Your research proposal will be assessed for:

• the coherence of your proposal;
• the relevance of the topic as it relates to the research of the Oxford Internet Institute and collaborating department;
• the clarity of research question(s), and the knowledge gap the proposal intends to fill;
• the appropriateness of the methods and research design as related to the research question(s); and
• the overall quality of the project proposed.

It is normal for your ideas to change in some ways as you commence your research and develop your project. However, you should 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. 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. The written work does not need to be data science related, but should demonstrate your critical and analytical capabilities and ability to present ideas clearly. 

The word count does not need to include any bibliography or brief footnotes. Extracts of the required length that originally come from longer essays are also acceptable.

This will be assessed for:

• a comprehensive understanding of the subject area, including problems and developments in the subject;
• your ability to construct and defend an argument;
• your aptitude for analysis and expression; and
• your ability to present a reasoned case in proficient academic English.

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
• Department open days
• Funding information from the institute
• Academic and research staff
• Research at the institute
• 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

Other courses to consider

You may also wish to consider applying to other courses that are similar or related to this course:

View related courses

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.

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• Visit HDR UK Futures

HDR UK-Turing Wellcome PhD Programme in Health Data Science

This truly outstanding and generously funded four-year programme at top UK universities provides you a pathway to join the UK’s leaders in health data research.

What this unique PhD programme offers you

Four-year programme: An initial foundation year allows students to gain real experience and insight into health data research.

Hosted by leading universities: Our host universities are among the very best in health data research.

Nurturing each student: Our programme aims to identify the particular abilities and interests of each student, and gear their PhD experience to effectively develop them.

Leadership Programme: Students benefit from a bespoke expert-led programme to develop the skills they need to understand, collaborate and influence others.

Generous funding: Students have their tuition fees (UK Home rate), college fees (where applicable), research expenses and travel costs paid and receive an enhanced, tax-free stipend with increases every year. (Y1 outside London: £23,955, Y1 in London: £25,954)

Building networks and experience: We actively support students in building networks and contacts in academia, the NHS and industry as well as taking internships and other opportunities to gain real-world experience. This includes a post-PhD bursary to support your next career step.

Team spirit: Strong relationships are built between our entire cohort of students through joint activities that build a genuine team spirit.

Personal support:  Each student has their own Director of Studies who is an additional point of contact during their time with us. All students are also further supported by the PhD team.

“The PhD programme has enabled me to gain first-hand experience in modern health data science approaches. It’s a truly unrivalled opportunity.”  Steven Wambua

Who is the PhD programme for?

We recruit enthusiastic, talented students who want to use data-driven research to develop and shape the UK’s response to the most complex health challenges of our times.

Applicants must have (or be on track to obtain):

• A first class or 2:1 undergraduate degree in statistics, mathematics, computer / data science, physics or an allied subject  or
• Another undergraduate degree subject and outcome but can demonstrate their suitability for this programme through additional qualifications or research experience.

Active or currently registered health care professionals   are not eligible and should consider the Wellcome PhD Fellowships for Health Professionals .

Applicants also need to meet the following criteria:

• Successful admission to the specified degree programme at one of our partner universities. Students will be expected to meet the admissions requirements of that department and university but do not need to hold the offer at the point of application.
• Two satisfactory academic or relevant references.
• Proof of a legal right to study in the UK or ability to satisfy the current requirements of UK Visa and Immigration.

Training is in-person, hybrid and virtual throughout the first year.

We are committed to a diverse and inclusive research culture . We welcome those who are returning from the workplace, international candidates and everyone underrepresented in STEM and academia. For further details see our FAQs .

We cannot accept applicants who are looking for a part-time PhD or those who are aiming to study whilst continuing to be employed elsewhere.

We aim to accommodate specific needs and personal circumstances. Please make us aware of individual circumstances when applying or contact us directly at  [email protected] . Please note our  applicant privacy notice .

If you have questions or require adjustments to the application process, please contact us below via email or telephone (+44 (0)770 847 8846).

There are no nationality restrictions and international students are able to apply. However, applicants are advised the award only covers fees at the UK/Home level. International students will be required to secure an additional scholarship from Queen’s University Belfast (after receiving a offer from us at interview) to cover the difference between Home and Overseas fees. This will limit the university choices available:

(Please be aware that these are usually highly competitive and will need to be applied for separately in your application to Queen’s University Belfast post-offer. A successful application to the PhD programme does not guarantee a fee waiver or scholarship. We do not accept applications from candidates who are self-funding.)

We are currently only recruiting for Queen’s University Belfast.

These are only initial programmes of study for Year 1. Students may transfer to a new university programme from Year 2 after research projects have been confirmed.

Is this the PhD future for you?

Watch our Applicant Open Day hosted by our current students to find out more about the programme and whether it’s for you.

Applications are currently: Closed

The application process.

Details required:

• Contact details
• Details and transcripts of university qualification(s)
• Any relevant job history
• Answers to personal-statement type questions (250-words maximum for each answer)
• Contact details for two referees
• There is no need to apply to the university, submit a research proposal, provide IELTS scores or contact supervisors at this stage

Submitted applications will first be checked for eligibility and then will undergo a first stage review. This will involve triage by the PhD Team in April 2024 . Successful applicants will be invited to an interview in May 2024 .

After receiving an offer, applications will be invited to apply to Queen’s University Belfast.

Selection criteria

Applicants should demonstrate that they meet the following criteria:

* These criteria will be assessed at interview via a pre-interview exercise.

HDR UK reserves the right to reject applicants who do not meet the criteria at any stage. Regretfully, we can only provide feedback for candidates who reach interview.

Programme Structure

The four-year programme is divided in two. There is an initial Foundation Year followed by a three-year research project. The first year combines the best in university-based training with HDR UK-led national activities. And we support students to produce game-changing research plans and their projects are backed by substantial research funding.

Foundation year

3-5 day immersion events allow students to gain insight into the work of HDR UK, and our academic, clinical and industry partners. Courses may be residential (expenses provided) with up to a week away from their home university or online. Students undertake an intensive deep dive into an important area of health data science. Immersion topics include risk prediction, oncology, clinical trials, epidemiology and bioinformatics. Past immersion weeks have been hosted by the Universities of Birmingham, Manchester, Oxford and University College London and the European Bioinformatics Institute.

The immersion events encourage students to work together and stimulate new interactions:

• Axes of Prognosis
• The Different Facets of Data

Research areas

PhD research projects can be linked to The Institute’s:

• Research priorities
• Research hubs
• Partnerships

Team working

Students operate as a national cohort and work collaboratively with others, overcoming traditional institutional silos. Students are registered with a  partner university  but can draw on academic expertise from across the HDR UK network and are supported to formulate research activities that bring together experts from across the UK.

• You can contact us at [email protected]   or phone (+44 (0)770 847 8846). 
• For details of how we process applicants’ data see PhD Applicant Privacy Notice .

Students have access to graduate-level courses and research project rotation in their university to introduce them to different areas of health data science and enable them to develop a bespoke research project under the guidance of our expert university leads.

Regular workshops and short courses introduce students to the work of HDR UK experts across our hubs, themes and priority areas and to external organisations. Past contributors have included NHSX, IQVIA and AstraZeneca.

Immersion and workshop events allow students to better understand the wider health and social care landscape and accelerate their potential to become sector leaders. They also enable students to develop more ambitious PhD research projects by stimulating collaboration with external academics, industry-based organisations, or by using national data infrastructure.

Training is provided by academic, industry and NHS experts to promote personal and professional development in leadership capability, cross-sector collaborative skills and inter-disciplinary working. In particular, HDR UK is committed to working with public and patients to build increased trust in health data research as well as designing solutions focused on improving patient outcomes and experience. Students will develop communication and collaborative skills to help put them at the forefront of this mission.

At the end of the Foundation Year students design a bespoke three-year research project and a multi-disciplinary supervision team based on their training experiences.

Research proposals will be rigorously reviewed by expert academics and public-patient representatives to ensure they are of the highest standards in terms of ambition, scientific methodology and impact on patient outcomes.

The research will be carried out at their home university and could be linked to HDR UK  research priorities ,  research hubs  or  partnerships .

This includes short immersions plus  longer practical real-world projects with businesses and other organisations at the cutting edge of everything from medical devices, to life sciences, to vaccines. Students also learn about leadership theory and attend specially-convened seminars from senior figures in relevant areas of healthcare.

Networks and experience: Students will be actively supported in building networks and contacts in academia, the NHS and industry as well as taking internships and other opportunities to gain real-world experience.

Team working: Students operate as a national cohort, building strong relationships through joint activities and overcoming traditional institutional silos.

Workshops: Regular workshops and short courses introduce the work of HDR UK experts and to external organisations.

Immersion events: These allow students to better understand the wider health and social care landscape and accelerate students’ potential to become a sector leader. They also enable them to develop an ambitious PhD research project.

Researcher development: Training is provided by academic, industry and NHS experts to promote personal and professional development in cross-sector collaborative skills, communication and inter-disciplinary working.

“Our Leadership Programme will give PhD students the chance to develop the practical skills they need to bring people together to use health data science to deliver much-needed innovations and advances in health and care,”  Professor Peter Bannister

Our partners

Programme partners include NHS Digital, AstraZeneca, Moorfields Eye Hospital NHS Foundation Trust, and University Hospitals Birmingham.

More broadly it will work with winners of the NHSX AI Innovation Award , which funds and supports promising artificial intelligence technologies in health and care. There will also be opportunities with businesses on the DTI listed top 100 digital health innovators which are using big data for healthcare innovation.

Master’s Degree Scholarships

We offer 10 annual Master’s degree scholarships worth £10,000 for students with an interest in dementia or diabetes research.

Undergraduate Summer Internship in Health Data Research

Apply for a summer work placement in health data research at a UK research organisation, with an HDR UK-Wellcome Biomedical Vacation Scholarship

Join the HDR UK Alumni Network

HDR UK’s online Alumni Network brings together the amazing people who have been part of our training and education programmes.

Our host universities

- - - - Meet our PhD students

Our PhD students come from a wide range of backgrounds - discover who they are and what their experiences have been as part of the PhD programme

Meet the PhD Programme team

Our wider team consists of leading experts in disciplines including theoretical physics, computer science, mathematics and statistics, applied mathematics and biochemistry.

• Miguel Bernabeu – University of Edinburgh
• Ioanna Manolopoulou – University College London
• Niels Peek – University of Manchester
• Iain Styles – Queen’s University Belfast
• Paul Taylor – University College London
• Catalina Vallejos – University of Edinburgh
• Angela Wood – University of Cambridge
• David Wong – University of Manchester
• Tom Nichols – University of Oxford
• Magnus Rattray – University of Manchester

Data Science Scholarships in UK for International Students 2024-2025

University of Hull Artificial Intelligence and Data Science Bursaries 2024

The University Hull scholarship application is now open for full time study in the 2024/25 academic year. This scholarships is to support widening participation students in studying the MSc Artificial Intelligence and Data Science.

Published: 2024-01-30 Type: Masters Study in: Kingston upon Hull Deadline: April 7, 2024

University of Birmingham AI and Data Science Scholarships for Masters Students to Study in UK 2024

The University of Birmingham is offering AI and Data Science Masters Scholarships in 2024-2025 for nine Masters programmes to upskill students from under-represented backgrounds to progress into the AI and Data Science workforce. This will include over 100 students from under-repre

Published: 2024-01-18 Type: Masters Study in: Birmingham Value: £10,000 Deadline: August 31, 2024

University of Liverpool 2024 Health Data Science MSc Scholarships

At least two scholarships covering the tuition fees for the MSc Health Data Science, up to a maximum amount of £10,850, are available for students starting the master's programme in the academic year 2023/24.

Published: 2023-11-16 Type: Masters Study in: Liverpool Deadline: Not Specified

UWE Bristol 2023 OfS Scholarships for MSc Data Science

These scholarships are funded by the Office for Students and are intended to increase the proportions of traditionally underrepresented groups in Data Science and Artificial Intelligence (AI). They are worth £10k per successful applicant and are to be used for course fees and eq

Published: 2023-06-28 Type: Masters Study in: Bristol Deadline: July 28, 2023

Best UK Scholarships

• Masters Scholarship at University of Birmingham 2024
• British Council GREAT Scholarship at University of York 2024
• University of East Angelia Black Scholarship for Undergraduate UK Students 2024
• University of Leeds School of History International Excellence Scholarship for Postgraduate Students 2024
• University of Edinburgh Global Online Learning Masters Scholarships 2024
• University of Leeds School of Media and Communication Excellence Scholarship for International Students 2024
• Swansea University Eira Francis Davies Scholarship for Female Students 2024
• British Council Research Fellowships at University of Edinburgh 2024

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PhD in Statistics

Study with leading statisticians at a world-class university

  Applications for entry 2024/25 are open  

Funding deadlines: 15 January 2024 (Applications received by this date will be considered for available studentships; we may also be able to consider applications received by the end of March for funding, but this is not guaranteed.) Final application deadline: 23 May 2024  

How to Apply

A PhD offers the chance to undertake a substantial piece of supervised work that is worthy of publication and which makes an original contribution to knowledge in a particular field. Our PhD programme is designed to produce professional social scientists, well versed in a range of advanced statistical techniques and methods, in addition to having an in-depth knowledge of your topic of interest. 

The Department of Statistics is one of the world's leading centres of quantitative methods in the social sciences and has long been home to some of the world's most famous and innovative statisticians. Today, the department has an international reputation for the development of statistical methodology that has grown from our long history of active contributions to research and teaching in statistics. 

Our core research areas are:

• Data science
• Probability in finance and insurance
• Social statistics
• Time series and statistical learning

If you have any questions about our MPhil/PhD Statistics programme, please  email the Research Manager .  

Research environment

The Department of Statistics at LSE is one of the oldest and most distinguished in the UK. It has a rich research portfolio covering core areas of statistical inference and real applications, particularly in the economic, financial and actuarial, social and industrial arenas. The close collaboration with other LSE departments, our London location and strong international partnerships are reflected in the research life of the Department of Statistics through the members of staff, PhD students, postdoctoral research fellows and the thriving visitor and seminar programmes.

Research in the department is concentrated in the following areas and PhD proposals should normally be linked to one of these areas:

Data Science

Research in the data science area is concerned with the development of new machine learning and statistical methods, and their applications. The areas of applications include the design of novel methods for understanding user behaviour, analysis of social data, modelling and inference for information cascades and epidemic processes that arise in social networks and biomedical applications, as well as algorithms for development of next-generation artificial intelligence systems.

Possible areas of research include:

• Bayesian inference and predictions
• Functional data analysis
• High-dimensional statistics
• Machine and statistical learning for relational data
• Network data models, inference and predictions
• Optimisation and machine learning
• Reinforcement learning
• Statistical learning methods in precision medicine
• Statistical models and inference for ranking data
• Stochastic models of epidemic processes
• Stochastic optimisation methods
• Stochastic processes in econometrics and finance

For more information about potential supervisors and their areas of interest, visit the Data Science research group .

Probability in Finance and Insurance

PhD research in probability in finance and insurance encompasses many aspects of the discipline. Methodological and theoretical research is mainly guided by applications with the aid of both academic and industrial experts, covering topics of modern stochastic finance with an emphasis on insurance and financial mathematics.  Applications include pricing and hedging exotic products, counterparty risk, portfolio optimisation, risk management and insurance, risk transfer and securitisation, etc. 

Research topics may be identified in advance by the applicant or may be arrived at through communication with a potential supervisor. The relative emphasis on methodology/theory vs. application may vary. 

Suggested research areas of PhD research projects include:

• Energy markets
• Excursions of Lévy processes and applications in finance and insurance
• Financial market with frictions
• Information asymmetry
• Interface between insurance and finance
• Lévy processes
• Optimal stopping
• Point processes in insurance and credit risk
• Quantile options and options based on occupation times
• Stochastic analysis and its applications in financial mathematics
• Stochastic control and analysis of partial differential equations in mathematical finance

This list is indicative only and by no means exhaustive. For more details about supervisors and their areas of research interests, please see the  Probability in Finance and Insurance research group . You will find links to the web pages of individual members of staff here. If you are interested in applying to undertake PhD research in probability in finance and insurance, you are welcome to contact one of these members of staff regarding a suitable topic for your research proposal. 

Social Statistics

PhD programmes of study in social statistics typically include both methodological development and the application of statistical methods to a social science field or to address new developments in social data, such as in sample surveys or social networks. Research topics may be identified in advance by the applicant or may be arrived at through communication with a potential supervisor. The relative emphasis on methodology/theory vs. application may vary. 

• Analysis of complex survey data
• Disclosure risk assessment and statistical disclosure control
• Estimation from survey data (and related data), taking account of nonresponse and using auxiliary information
• Latent transition and latent class models for modelling diagnostic tests
• Latent variable models and structural equation models for categorical data
• Longitudinal data analysis, especially event history (survival) analysis and dynamic panel models
• Modelling response strategies and detection of outliers in educational and behavioural sciences
• Multilevel simultaneous equations modelling of correlated social processes

For more details about potential supervisors and their areas of interest, visit the  Social Statistics research group . If you are interested in applying to undertake PhD research in social statistics, you are welcome to contact one of these members of staff regarding a suitable topic for your research proposal.

Time Series and Statistical Learning

PhD research in time series and statistical learning encompasses many aspects of these disciplines. We are keenly involved in both theoretical developments and practical applications. Current areas of interest include time series (including high-dimensional and non-stationary time series), data science and machine learning, networks (including dynamical networks), high-dimensional inference and dimension reduction, statistical methods for ranking data, spatio-temporal processes, functional data analysis, shape-constrained estimation, multiscale modelling and estimation and change-point detection.

Research topics may be identified in advance by the applicant or may be arrived at through communication with a potential supervisor. The relative emphasis on methodology/theory vs. application may vary.

Suggested PhD research areas include:

• Automating statistical advice
• Change detection for complex data
• Dimension reduction and factor modelling
• Estimation of stochastic volatility models
• Financial econometrics
• Functional data analysis including functional time series
• High-dimensional time series analysis
• High-dimensional variable selection
• Infectious disease modelling
• Inference for sequential data including change detection in multiple data streams
• Network time series analysis
• Nonparametric and semiparametric regression
• Non-stationary time series analysis
• Reinforcement learning for time-dependent data
• Robust statistical analysis for high-dimensional data
• Shape-constrained methods
• Spatial econometrics modelling
• Spatio-temporal modelling
• Statistical analysis of high-dimensional multi-type recurrent events

For more information, please see the  Time Series and Statistical Learning research group . 

PhD Programme Structure

PhD Your application

PhD Funding Opportunities

FAQs Frequently Asked Questions

PhD Handbook Our guide for current students

Past PhD students A listing of our PhD graduates

Visiting Research Students How to apply

PhD Academy A dedicated space for PhD students

Graduate Career Destinations What our PhD graduates have done next

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Fully-funded PhD Studentships in Computer Science

Up to 20 fully funded PhD studentships in all research areas in Computer Science.

Application deadline

Funding source, funding information.

• UKRI stipend (£16,062 from October 2022) plus £3,000 per annum for full-time students; 50% of these amounts for part-time students.
• Tuition fees are also covered.
• £3,000, total, to support conference attendance and other relevant costs.  

The Department of Computer Science at the University of Surrey is offering up to 20 fully funded PhD studentships (at UK rates) to strengthen its research. Studentships are available for the duration of 3.5 years (or 7 years at 50% time) in all areas of its research portfolio, which includes in cybersecurity and cryptography, distributed and concurrent systems, artificial intelligence and machine learning.

Successful applicants will become part of a vibrant PhD community and will benefit from the strong research environment and high international visibility of the Department. 

You may also be interested in our specific funded PhD projects in computer science .

Eligibility criteria

Open to UK nationals, those with EU settled or pre-settled status, or indefinite leave to remain

We expect successful applicants to hold a BSc degree (with at least UK 2:1 honours, or equivalent) or an MSc degree with distinction in Computer Science or a related discipline.

The standard English language requirement is for a score of 6.5 or above (or equivalent) with 6.0 in each individual category, in an IELTLS Academic test taken in the last 2 years. Equivalent qualifications are listed on our language requirements page .

How to apply

Applications should be made via the Computer Science PhD programme page on the “Apply” tab.

You would need to identify an appropriate area of research, and preferably identify one or more potential supervisors and provide a brief research proposal to assist in matching with supervisors. For research areas, visit the Computer Science PhD programme page .

Applications will be assessed on an ongoing basis until all studentships have been allocated. We recommend you apply early.

To apply please upload your CV, copies of all degree certificates and transcripts, and the contact details of two referees (ideally, arrange for their letters of recommendation to be added to your application), and provide a covering letter identifying research area and preferably also potential supervisors and a brief research proposal.

Interviews will be conducted remotely over Zoom or Teams.

Studentship FAQs

Read our  studentship FAQs  to find out more about applying and funding.

22 July 2022

Contact details

Applicants are welcome to approach potential supervisors using contact details from the Department website to seek more information in advance of applying.

Studentships at Surrey

We have a wide range of studentship opportunities available.

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MSc Data Science Pathways Scholarships

Primary page content.

The pace at which we produce data is rapidly outstripping our ability to analyse and use it. Science and industry are crying out for a new generation of data scientists who combine the statistical skills of data analysis and the computational skills needed to carry out this analysis on a vast scale. 

The curriculum of our MSc Data Science provides students with these skills, and trains them for specific domains via programme pathways. 

These partial tuition fee waiver scholarships will support full-time students who have applied for this Masters programme.

Number available

Year of entry, eligibility criteria.

• The scholarship is open to both home and international students
• MSc Data Science and Artificial Intelligence
• MSc Data Science and Econometrics
• MSc Data Science and Financial Technologies
• MSc Data Science and Marketing

Application deadlines

Applications are now closed.

Please note that it can take several weeks for programme applications to be processed and for places to be offered. No late scholarship applications can be accepted. 

How to apply

Please write a short (maximum 500 words) statement that includes the following information: 

• A description of the broad areas of data science work and/or research that you have taken since your undergraduate degree (if any) and that you intend to explore at postgraduate level 
• Background information outlining your personal journey to a career in data science (or the data science pathway of your choice)

This statement should then be sent to Dr V L Raju Chinthalapati ( [email protected] ) by the deadline above.

Selection process

Applications will be reviewed and the awards will be made by staff teaching on the MSc Data Science programme in the Department of Computing .

• Find a course
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Data Science Scholarships (OfS)

Birkbeck is offering scholarships for students on the PG Cert Applied Data Science and MSc Data Science .

In March 2023, the government announced that it would support the development of degree conversion courses in artificial intelligence (AI) and data science technologies to help address the shortage of AI and data specialists in the UK. In response, the Department for Science, Innovation and Technology (DSIT) and the Office for Artificial Intelligence (OAI) are providing funding through the Office for Students (OfS) for providers to develop postgraduate conversion courses in these areas.

Value of funding

• Successful applicants will be provided with a £10,000 scholarship. After deduction of your course fees, any remaining amount will be paid in equal instalments over the period of your full-time or part-time study. 
• PG Cert Applied Data Science: October 2024
• MSc Data Science: October 2024 or January 2025

Eligibility

• If you wish to be considered for a scholarship, you must :
• have a current application for the  PG Cert in Applied Data Science or MSc Data Science at Birkbeck
• be self-funding your degree, and not in receipt of any other scholarship or sponsorship
• apply for the scholarship before the posted deadline, and
• meet at least one of the eligibility criteria set out in the section below.
• All applications will be assessed and priority will be given to eligibility criteria a) to c) as stipulated by the OfS.
• Applicants who do not meet any of the criteria below will not be considered for a scholarship.
• a)  21, Black or Black British - Caribbean; 22, Black or Black British - African; 29, Other Black background; 41, Mixed - White and Black Caribbean; 42, Mixed - White and Black African. 
• In line with the HESA student ethnicity codes 2018/19 ( HESA student ethnicity codes ).
• b) Female: Applicants who are ‘female or identify as female’ gender. The Office for National Statistics describes female gender as “a social construction relating to behaviours and attributes based on a label of femininity. Gender identity is a personal, internal perception of oneself and so the gender category someone identifies with may not match the sex they were assigned at birth where an individual may see themselves as a woman.”
• c) Disabled: You are disabled under the Equality Act 2010 if you have a physical or mental impairment that has a ‘substantial’ and ‘long-term’ negative effect on your ability to do normal daily activities. 
• ‘Substantial’ is more than minor or trivial, e.g. it takes much longer than it usually would to complete a daily task like getting dressed. 
• ‘Long-term’ means 12 months or more, e.g. a breathing condition that develops as a result of a lung infection. 
• There are special rules about recurring or fluctuating conditions, e.g. arthritis.
• d)  From indices of deprivation decile 1 to 4.  Check to see if your area is in indices of deprivation decile 1 to 4 . 
• e) Care experienced. A care experienced person is someone who has spent time in care during their childhood.
• f) Estranged. An irreconcilably estranged person is someone who has not had any verbal or written contact with their parents for a significant period of time, and this is unlikely to change. This can include your biological or adoptive parents, or your only living parent. A significant period of time is usually considered to be twelve months or longer, but this can also depend on your circumstances.
• g)  Gypsy, Roma, Traveller. The term Gypsy, Roma and Traveller encompasses a wide range of individuals who may be defined in relation to their ethnicity, heritage, way of life and how they self-identify. This may include:
• English or Welsh Romany Gypsies
• European Roma
• Irish Travellers
• Scottish Gypsy Travellers
• show people such as people linked with fairground or circus professions
• people living on barges or other boats
• people living in settled (bricks and mortar) accommodation
• New Age Travellers
• h) Refugee. The definition of a Refugee as defined on the UKCISA website is that you must be ordinarily resident in England on the first day of the first academic year of your course; and you must have been recognised as a refugee by the UK Government and have remained ordinarily resident in the UK and Islands since then;  OR  be the spouse/ civil partner of such a refugee and have been in that relationship on the date on which he/she made his/her application for asylum; OR  be the child of such a refugee, or the child of such a refugee's spouse/civil partner, and be able to show that on the date that refugee made his/her application for asylum, you were under 18 years of age; and the refugee was your parent, or your parent's spouse/civil partner.
• i)  Child from UK military family, veterans or partner of UK military personnel. From a military family, where immediate family member (partner, child, sibling) is or was part of the UK military/ military personnel/a veteran.

Application deadline

• 5pm, Monday 19 August 2024.
• Please read the below guidance before applying.
• Personal details
• Please complete the personal information and contact details section of the form - we need this information to contact you about your application. 
• Eligibility criteria  
• Scholarships are aimed specifically at supporting graduates from underrepresented groups in the Artificial Intelligence and Data Science fields stated by the Office for Students. Hence, the information you provide us with in this section will help us in establishing your eligibility for the scholarship. Please note that this section is an important part of the selection process. 
• Please be sure to tick the box(es) that best describes your situation and that you can provide the necessary proof if requested. 
• Course details 
• Please enter the title of the course you are applying for and the year and month your course starts. 
• Personal statement 
• When answering the questions in the personal statement section of the form please consider the following. In making a judgement about your application, the selection panel will base their assessment on: 
• Your personal and family circumstances and the barriers that you have faced in continuing your education - with particular reference to the underrepresented group(s) you belong to. 
• Your ambitions for the future, why you have chosen to study this course and how the scholarship will help you to achieve your ambitions. Your application for the scholarship is completely confidential and the selection panel will only be able to take into account information that you provide on your application form. Whilst the selection panel do need some details of personal circumstances, with particular reference to the underrepresented group(s) you belong to, please note that we do not need to know about the circumstances that led to you being included in particular groups if you do not wish to provide this information (although it may help in some circumstances). Please also note that, as the scholarship is funded by the OfS, anonymised data may be supplied to OfS for accountability purposes. 
• The supporting statement should be no more than 500 words. Please make sure to adhere to this limit. We have also provided some prompts on what to include in the application form.
• Apply for the Data Science Scholarships (OfS) scholarship via the online application form .

Application outcome

• Please note that this is a competitive process and not all applications will be successful. There is no appeals process if you are not successful as the panel’s decision is final; also, please note that we will not be able to offer feedback.  All applicants will be notified of the outcome of their application by Wednesday 25 September.
• You are welcome to reapply in the next intake if you are unsuccessful. If you are successful in being offered a scholarship, you will be notified soon after the assessment, and we may ask for further details including bank account details.

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AI and Data Science Postgraduate OfS Scholarship

Find out how the scholarship might help you, if you are eligible, and how and when to apply.

New introduction

Funding of up to £10,000 for 10 postgraduate artificial intelligence and data science students from underrepresented backgrounds.  Check if you’re eligible, and how to apply.

• Value: £10,000 awarded against tuition fees, the remainder paid as a cash bursary in one instalment. This will be paid pro-rata for part-time students.
• Study level:  Postgraduate — new students in their first year only
• MSc Artificial Intelligence
• MSc Data Science
• Applications:

Deadlines for applying: 

• Applications for September 2024 entry open 15 May 2024
• Applications close 8 July 2024

Aim of the scholarship

The Office for Students (OfS) has awarded funding to a collection of universities to help address the shortage of AI and data specialist in the UK and underrepresentation within the industry. 

We are looking for a new generation of idealists, visionaries and problem solvers to help businesses, industry and government make the right decisions in our increasingly complex and uncertain world. 

Check if you can apply

To apply, you must:

• Be eligible for a Masters Loan from the Student Loans Company and have a UK Student Support Number

In addition, applicants must meet one of the following criteria:

• Black (as defined by  HESA student ethnicity codes )
• have a registered disability
• students from areas of the UK where young people are less likely to go on to higher education (Polar quintiles 1 and 2 as per  HESA guidance )
• care experienced student
• estranged student
• Gypsy, Roma, Traveller
• child from military family, veteran, and partner of military personnel

If recognition of prior learning or any other prior learning credits/experience are applied which reduce the number of taught credits, you will no longer be eligible for the scholarship.

If you have any questions about whether or not you meet the eligibility criteria, please contact  [email protected] .

Check the terms and conditions

Before you apply, read our terms and conditions.

They explain:

• what’s expected of people who get scholarships
• what happens if you leave your course or we withdraw the scholarship
• how we use your personal information

You’ll need to:

• complete the application form. Applications open on 15 May 2024.

You must apply by 8 July 2024. We will not consider late applications.

Terms and Conditions

By accepting the offer of the scholarship, you are accepting these terms and conditions..

Please read them carefully and keep a copy for your records.

The University may withdraw the scholarship in the following circumstances and the implications are set out below:

• You are subsequently found to be ineligible for the scholarships or if these terms and conditions are not met in full. Your scholarship will be cancelled and you will be required to repay the scholarship in full/full tuition fees will be due.
• You suspend your programme, withdraw from your course or are withdrawn by us. All scholarships require satisfactory progress on your course. You will not be eligible for the full scholarship if you do not complete the full course, which results in a fee reduction. If you withdraw, suspend or exit with a lesser award the  Regulations for the Payment of University Fees  confirm that the discount/scholarships will be pro-rated if tuition fees are reduced. In this circumstance, the value of the scholarship will be pro-rated in proportion to the tuition fees charged on your eligible course.
• You do not pay outstanding tuition fees when due to us.
• You make a change to your course. If you intend to make any change to your course please check with the university what impact this will have on your scholarship. If you transfer courses or change your study mode you will no longer be eligible for the scholarship. In these circumstances, the value of the scholarship will be pro-rated in proportion to the tuition fees charged on eligible course(s).
• You do not meet all conditions attached to your offer of a place at the University.
• You fail to meet the key student requirements or any of these scholarship terms and conditions. Your scholarship will be cancelled and you may be required to repay the scholarship in full/full tuition fees will be due.

FURTHER INFORMATION

The university reserves the right to amend its scholarship provision without notice.

A scholarship offer must be accepted by the given deadline. Where an offer of a scholarship is not accepted by the given deadline it is automatically revoked unless otherwise agreed with the university.

Scholarships may not be deferred to the next academic year.

All students are required to comply with the  University’s Terms and Conditions  applicable to the provision of the University’s Educational Services (and the regulations, policies and procedures referred to within), as provided to applicants with their university offer letter and as updated from time to time.

There is no cash alternative to the scholarship award and awards are not transferable.

Where appropriate, personal information will be sent to the external provider via email, with the documentation encrypted and password protected. The password will be provided via a separate means, for example, via telephone.

For further detail, please see the  Regulations for the Payment of University Fees.

The scholarship terms and conditions will continue even if you are no longer registered as a university student. For example, the conditions related to repayment of scholarship award or any obligations you agreed to undertake following completion of your course will still apply.

These terms and conditions do not constitute a relationship between us of partnership, joint venture, principal or agent. They are between you and us and no other person shall have any rights to enforce any of their terms.

These terms and conditions will be governed by the laws of England and Wales and we both submit to the Courts of England Wales.

Any dispute or complaint arising in connection with the scholarship should be addressed in writing in the first instance to  [email protected] .

Privacy Notice

This privacy notice explains who we are, how and why we collect and use personal information about you, what personal data is collected and held about you for the  scholarship, our purposes and lawful bases for processing, who we share your personal data with, relevant retention periods, and how you can exercise your privacy rights.

This notice provides information that is in addition to information contained in the university’s general scholarship privacy notice ( Privacy Notice for Student Scholarships ). Please do read this notice to understand our practices and if you have any questions please contact us using the contact details provided below.

Who we are and what we do with your information

The university is the Controller in respect of the personal data you provide as part of your application onto the scholarship.

The university is registered as a Controller with the Information Commissioner’s Office (ICO). We manage personal data in accordance with the General Data Protection Regulation (GDPR) and the university’s data protection policy.

In order for Manchester Met to consider you for this scholarship, your application (if applicable) will be considered for eligibility onto the scheme. All eligible students will receive an email confirmation if they are eligible for the scholarship, which includes the scholarship terms and conditions. Students who do not want to accept the scholarships terms and condition should email Manchester Met and reject the scholarship. Externally funded scholarships work in the following way:

• Students who meet the scholarship terms and conditions will need to apply via the online form to be considered for these scholarships, after researching on the scholarships website which scholarship they would like to apply for.
• Applications are assessed by the appropriate scholarship panel which consists of staff from both Manchester Met and, if applicable, by Coventry University and eligibility considered by further review of the student’s University application (at which point, students are contacted after the deadline date with an update).
• Unsuccessful students will also be contacted by a panel member via email. Application data for unsuccessful students will be deleted within a month after the deadline date.

The personal data we process

For this scholarship, we collect and process certain data about you, including information of a sensitive nature. This includes information detailed in your application for the scholarship.

If you contact us, we may also keep a record of that correspondence.

The purpose of the processing

What is the use of personal data.

Information within your university application form and scholarship application email in order to apply for the scholarship.

What is the lawful basis?

Necessary for the performance of a contract (Article 6(1)(b)).

The recipients or categories of recipients of the personal data

We will disclose personal data about you to the following third parties:

• Coventry University, anonymised scholarship scores
• Student Billings, Admissions, Programme Lead or Panel Members

The right to withdraw consent

If we have collected and processed your personal information with your consent, then you can withdraw your consent at any time. Withdrawing your consent will not affect the lawfulness of any processing we conducted prior to your withdrawal, nor will it affect processing of your personal information conducted in reliance on lawful processing grounds other than consent. You can withdraw your consent by writing to  [email protected]  stating your name, your student ID number and in the e-mail subject state: ‘Withdrawal of consent’.

Data Retention

Your personal data will only be retained for as long as it is necessary in accordance with the University’s Retention and Disposal Schedule. 

Your rights in respect of the processing

The GDPR provides data subjects with the following data subject rights:

• The right to be informed – this privacy notice assists with fulfilling these obligations
• The right of access
• The right to rectification
• The right to erasure
• The right to restrict processing
• The right to data portability
• The right to object

Please note, that these rights apply in certain circumstances, for example according to the lawful basis utilised by the University. The right of access to personal information held about you exists in order to be aware of, and verify, the lawfulness of the processing. Please use the contact information below to exercise these rights.

Contacting us

For questions or concerns about this privacy notice, or our use of your personal information, please contact  [email protected]  in the first instance.

Our Data Protection Officer can also be contacted using  [email protected] , by calling 0161 247 3884 or in writing to: Data Protection Officer, Legal Services, All Saints Building, Manchester Metropolitan University, Manchester, M15 6BH.

Right to lodge a complaint with the supervisory authority

You have the right to lodge a complaint with the Information Commissioner’s Office (ICO) as the supervisory authority in respect of the processing of your personal data. We would encourage you to expend our internal complaints procedure through our initial contact and the University Data Protection Officer, prior to contacting the ICO.

You can contact 0303 123 1113 or  [email protected] . Go to  further contact information.

Update to this privacy notice

We may update this privacy notice from time to time in response to changing legal, technical or business developments. When we update our privacy notice, we will take appropriate measures to inform you, consistent with the significance of the changes we make.

Get ready for a masters in Data Science and AI

If you’ve any queries about this or other scholarships, email [email protected] .

Data Science Online Scholarship (September 2023 and January 2024 entry)

The University of St Andrews is delighted to be able to offer a scholarship opportunity that can help you achieve your personal development goals. This exciting new Scholarship is  available to students wishing to undertake the new online course in Data Science (PG Dip or MSc).

Successful students will be awarded a contribution of up to £6,000 in total towards their course fees.

The award is open to entrants commencing online studies in September 2023 or January 2024.

At what stage of my course application can I apply for this scholarship?

You can apply for the scholarship after you have submitted your course application for a place at the University of St Andrews. You do not need to wait until you have received an offer of a place before applying for the scholarship.

Application restrictions

Study level.

Available to students studying at:

Available to students studying:

Domicile for fee status

Available to faculty members from:

Application assessment

Available to, mode of study, additional criteria.

Selection is based partly on financial need; you will need to provide a statement explaining your current household financial situation (not more than 250 words) and a course suitability statement (not more than 250 words) explaining the following:

Suitability statement 

• why you have applied for this course 
• how the course relates to your personal or professional ambitions 
• how your academic and professional background show you have the skills needed to work effectively at postgraduate level.  

How to apply

After you have applied to a new course beginning in academic year 2023, you will be provided with login details for the My application portal.

This scholarship is available to complete and submit through ‘View my funding applications’ in the Scholarships and Funding section of My application .

Scholarship deadlines

• September entry: 18 August 2023
• January entry: 31 October 2023

Scholarship application form guidance

Terms and conditions

Please read the University of St Andrews scholarships terms and conditions

(opens in new tab)

When will I know the outcome?

The outcome of your scholarship application will be available on View or continue my funding applications in the Scholarships and Funding section of My Application by late August 2023 for September 2023 entry and mid-December for January 2024 entry.

[email protected]

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Scholarships

For 2024 entry, the programme has been awarded 15 scholarships to disburse to students. These are valued at £10,000 each.

Data Science Scholarships

If you plan to study for a Master's in Health Data Science, you may be eligible for an Office for Students scholarship. There are up to 15 scholarships available for students commencing their studies in October 2024, each worth £10,000.

Welcome to MSc Health Data Science

The MSc in Health Data Science at Lancaster provides training and research excellence in Medical Statistics, Data Science and Global Health and aims to equip graduates with the necessary skills, knowledge and attributes for direct entry to professional health data science careers. The programme provides core training in computing (R and Python), statistical modelling, epidemiology and research methods, allows for specialism in Health Informatics or Global Health and provides the opportunity to complete a project as part of a placement with our national and international partners, which include the World Health Organization, the National Health Service, the Kenya Medical Research Institute, the Clinton Health Access Initiative, and more.

Data Scientists, data engineers and business analysts are among the most sought-after positions in the UK and internationally, and the health sector demand continues to grow.

Lancaster University’s MSc Health Data Science programme has been developed to address the growing demand for these skills in healthcare.

Potential career destinations for students graduating with an MSc in Health Data Science include, but are not limited to:

• Data scientists in the pharmaceutical, biotechnology, and bioengineering industries
• Data scientists in the NHS and allied organisations
• Civil-service careers in national-level health agencies
• International health organisations such as World Health Organisation, Médecins Sans Frontières, and the Red Cross

Applications to the programme are now welcome for study commencing October 2024 .

About the scholarships

The purpose of the scholarships is to widen access and participation to AI and Data Science roles for underrepresented groups. As such, the criteria are restricted and you should read carefully the documentation below to find out if you qualify. If you do not meet the criteria, please visit our general scholarships page as you may be eligible for one or more of Lancaster University's other scholarships and bursaries.

Eligibility Criteria

The following 3 groups will be given priority for the scholarships:

• Female students
• Black students (as defined by HESA ethnicity codes )
• Registered disabled students

Additional criteria that we will consider:

• Students from areas of the UK where young people are less likely to go on to higher education (POLAR Q1 and Q2)
• Care experienced students
• Estranged students
• Gypsy, Roma, Traveller students (resident in the UK)
• Refugees (resident in the UK)
• Children from military families, veterans and partners of military personnel

PLEASE NOTE : These scholarships are restricted to UK or EU citizens with settled status only, though this may change.

How to apply

Below you will find links to two separate documents. The first provides guidance to support your Office for Students scholarship application. Please read this first .

The second is the application form. If you have questions regarding the completion of the form, please email the Director of Studies, Dr Emanuele Giorgi .

1. Guidance for Conversion Master's Scholarships

2. OfS Funded Scholarships Application Form for Postgraduate Conversion Courses

Fully Funded Siemens Mobility and UKRI PhD Scholarship: Geographic Test Data Generation in the Railway Domain

Swansea university - computer science.

Funding providers : Siemens Mobility and UKRI

Subject areas:  Computer Science 

Project start date:  

• 1 July 2024 (Enrolment open from mid-June)

Project description: 

This will be a PhD project done in Collaboration with our Industrial Partner, Siemens Mobility.

Modern Railway Systems operate from accurate geographical maps called scheme plans. They contain the topology of the tracks, positions of signalling equipment, and conceptual constructs such as train routes, and may have thousands of elements. Due to the large quantity of possible data permutations, manual testing of the scheme plan data preparation system is a laborious process. To avoid that we aim at an alternative approach, via the automated generation of test data. These will be constructed following the European Train Control System(ETCS) standards involving significant domain knowledge to interpret the requirements. Coverage metrics will be added to understand how well a set of test data exercises the requirements. 

There are various approaches to solve this problem: 1) Via SMT solving or Constraint Solving, or 2) via AI/Optimization. [SMT solvers/constraint solvers are state-of-the-art Symbolic AI tools for verifying computer programs and are applied in Industry as part of quality assurance processes. The use of optimization techniques is an alternative and also quite promising in this context.] 

Interested candidates should have a strong interest/background in either Formal Methods/Mathematically derived techniques, or in Software Engineering/Testing, or in Artificial Intelligence.

Eligibility

Candidates must hold a UK bachelor’s degree with a minimum of Upper Second Class honours or overseas bachelor’s degree deemed equivalent to UK honours (by UK ECCTIS) and achieved a grade equivalent to UK Upper Second Class honours in Computer Science, Mathematics or a closely related discipline, or an appropriate master’s degree with a minimum overall grade at ‘Merit’ (or Non-UK equivalent as defined by Swansea University). If you are eligible to apply for the scholarship but do not hold a UK degree, you can check our comparison entry requirements. Please note that you may need to provide evidence of your English Language proficiency. 

Due to funding restrictions, this scholarship is open to applicants eligible to pay tuition fees at the UK rate only , as defined by UKCISA regulations.

Funding Details

Additional Funding Information

This scholarship covers the full cost of UK tuition fees and an annual stipend at UKRI rate (currently £18,662 for 2023/24).

Additional research expenses will also be available. 

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