The DPhil in Social Data Science provides an opportunity for students to formulate and address novel research questions at the intersection of the computational and social sciences, supported by the multidisciplinary faculty at the OII, Engineering Science, Statistics, Sociology, Computer Science and other departments across the University of Oxford, as well as by the complementary strengths of the student cohort, each of whom will be building on the literature from different disciplines.
Students are expected to pioneer new approaches to contemporary social problems, exploiting fast expanding possibilities in large-scale data collection, machine learning, and statistical modelling. This degree will train individuals to develop and adapt techniques such as machine learning to analyse large, structured and unstructured, complex datasets in order to improve decision making and answer social science research questions.
Beyond the technical skills, the programme will also provide students with a solid grounding in social science theory and methodology, and reflection on the consequences of the techniques applied. Ordinarily, students will be expected to have training similar to that offered within the MSc in Social Data Science, but gaps may be filled with courses from the MSc curriculum as well as other existing courses at the University.
Our DPhil students’ research spans a wide range of topics, normally linked to the research of one or more of our faculty supervisors. Most students will be supervised by two faculty members: one from the computational sciences and one from the social sciences.
This system allows doctoral students to dig deeply into research questions at the intersection of disciplines while also being able to place these questions within the broader disciplinary contexts.
Over the course the programme, you are expected to produce an important and original piece of scholarship that will make a significant contribution to the dynamic area of social data science. On completion, you will have the qualities and transferable skills necessary to excel in teaching, research, policy-making or business.
Whilst every doctoral project will follow a unique path, broadly there are 3 stages:
- Formulating a research question: You will focus on developing your research questions, and research skills. All doctoral students are required to take five foundation courses designed to give the necessary foundation for undertaking research in this multi-disciplinary field.
- Analysis: You will outline the structure of your thesis, which includes data gathering, analysis, and other steps. Many students also use this time to start drafting journal articles, often in collaboration with their supervisors.
- Writing up your thesis and submitting: You will concentrate on any final data gathering, analysis, experimentation and writing up the final chapters for submission of your thesis.
In addition to the formal requirements of the DPhil thesis, all doctoral students receive regular training in the key graduate skills necessary to support their research and future employment. These range from classes on specific tools or skills to more generic training such as presentation skills, academic writing and peer review.
We also provide opportunities for DPhil students to gain teaching experience through mentored assistantship roles in some of the MSc courses. There are also opportunities for taking part in organising the annual student-run Connected Life conference dedicated to sparking exchange between disciplines and showcasing emerging Internet research.
On completion of the DPhil programme, it is expected that you will:
- Demonstrate in-depth research experience in at least one of the social data science areas
- Be able to generate impact on the policy and design of socio-technical systems based on social data science research
- Have an in-depth knowledge of specific contemporary social and political science theories and data science approaches to tackling research questions related to these theories
- Have made an original contribution to the current state-of-the art for analysing large-scale human behavioural data and either have developed new methods and/or adapted existing methods to the specific challenges of data related to human behaviour
- Design, execute, document, and disseminate research that applies tools and methods from data science to address a social science research question
- Have the qualities and transferable skills necessary to excel in teaching, research, policy-making or business in your studied field, including abilities to design new technologies and to predict and analyse their impacts
How to Apply
All applications must be made through the University of Oxford Graduate Admissions site. Please ensure that you start the online application process as early as you can, to ensure plenty of time to complete your application. Only applications that are complete by the deadline can be considered by the admissions team.
- The full-time DPhil programme has two deadlines in November and January. Applications submitted for both deadlines are given equal consideration.
- The part-time DPhil programme has three deadlines in November, January and March. Applications submitted for all deadlines are given equal consideration.
Whilst every doctoral project will follow a unique path, there are common milestones that every DPhil student must pass. The information below gives a broad indication of the general milestones, but all students are advised to discuss the timeline with their supervisor.
During the programme you will move through three different stages:
- Probationer Research Student (PRS)
- DPhil Status
- Confirmed DPhil Status
|Stage 1: Formulating a Research Question
||Stage 2: Analysis||Stage 3: Writing Up and Submission|
|Entry as Probationer Research Student||Transfer to DPhil status||Confirmation of DPhil status|
|Foundations and Frontiers of Social Data Science||Thesis: analysis||Thesis: Writing up and submission|
|Applied Analytical Statistics|
|Research Design for Social Data Science|
|Foundations of Visualisation|
|Other training as agreed between student and supervisors|
|Thesis: formulating a research question|
* You can find detailed information on scheduling in the DPhil SDS Graduate Studies handbook.
Stage 1 usually occurs in Year 1 for full-time students and Years 1 and 2 for on the part-time programme.
All doctoral students are required to take courses which give the necessary foundation for undertaking research in this multi-disciplinary field. Courses must be passed in order to transfer from PRS to DPhil status.
Social Data Science students take five compulsory foundation papers, designed to provide students with core skills, methods, theories and concepts required to undertake the remainder of the degree. These include laboratory and practical exercises to ensure that students are competent with particular techniques.
DPhil students will also complete other training as agreed with their supervisors and the course providers. This may include content from the MSc in Social Data Science, the MSc in Social Science of the Internet, or partner departments involved in the Social Data Science programme.
In addition to these classes, students will be required to work on their thesis, and will meet regularly with their supervisor to this end. By the end of this stage, students will be expected to have formulated clear research questions and identified appropriate theoretical and methodological frameworks for addressing these questions.
Transfer of Status
As most students will enter the DPhil programme as Probationer Research Students (PRS), they will be expected to gather materials and draft a research proposal for transfer to DPhil Status between their third and fourth term in Oxford. Assuming the normal three-year programme, we expect students to complete the transfer interview by the end of their fourth term. Most students successfully transfer in the third term. Details of the Transfer of Status process can be found in the DPhil Graduate Studies Handbook.
Stage 2 usually occurs in Year 2 for full-time students and Years 3 and 4 for students on the part-time programme.
This stage of the DPhil will normally be devoted to data gathering, method development, analysis and mapping the outline structure of your thesis. However, students will also need to make significant progress in writing their thesis, drafting at least two chapters in preparation for the Confirmation of Status milestone. This may include a period of fieldwork away from Oxford. Many students also use this time to start drafting journal articles, often in collaboration with their supervisors.
Confirmation of Status
Confirmation of DPhil Status is an essential stage on the way to the doctorate and confirms that the student is capable of producing a thesis of the necessary standard and within an appropriate timescale. It is not possible to submit a thesis for examination until DPhil status has been confirmed: this applies to students who have transferred to the DPhil from an Oxford MLitt, MSc or MPhil as well as to those who enter as a PRS student.
The OII’s Graduate Studies Committee expects students to complete the confirmation interview by the end of the 9th term of study for full time students; and by the 18th term of study for part-time students. Details of the Confirmation of Status process can be found in the DPhil Graduate Studies Handbook.
Stage 3 usually occurs in Year 3 for full-time students and Years 5 and 6 for students on the part-time programme.
DPhil will concentrate on any final empirical work, and be writing up the final chapters for submission of the thesis. The thesis must be submitted within 12 terms (full-time) and 24 terms (part-time) from the date of admission as a graduate student. In special circumstances, you may apply for an extension of time through the Graduate Studies Committee. The maximum extension permitted is 6 terms, making 18 terms (full-time) or 30 terms (part-time) of study in all.
Once the thesis has been submitted, two examiners are appointed and the examination by viva voce (an oral defence of the thesis) is scheduled.
As a graduate student you will be assigned an academic supervisor, who is responsible for your academic well-being and progress. In addition to academic supervision, you will also have a college advisor who can help with issues of student support and welfare.
You should expect to meet with your supervisor at least four times a term. In the early stages of your doctoral studies your supervisor will assist you in settling into the pace of academic life, help you identify your training needs in order to fulfil your research and facilitate appropriate networking across the University. As your research progresses, your supervisor will advise you on research design, provide guidance on any data collection, and comment on your written drafts. In the final stages of your doctoral studies, your supervisor will provide comments on your thesis drafts and help you prepare for milestones and the final examination of the thesis. Your supervisor may also provide career guidance as you plan your future beyond your period of study.
The following faculty members are eligible to supervise DPhil students. The supervision areas are intended as a guide only: please contact a faculty member directly if you would like to discuss their suitability to supervise your research proposal.
- Dr Adam Mahdi, Institute of Biomedical Engineering (Machine learning, signal processing, modelling, symbolic computation)
- Prof Andy Przybylski (Psychology, human motivation, video games, virtual environments)
- Prof Balazs Vedres (Creative teams, diversity and discrimination, social networks and success)
- Dr Bernie Hogan (Behaviour, big data, ethics, social networks, social network analysis, social media, virtual communities, identity, algorithms, real names)
- Dr Brent Mittelstadt (Ethics, medical ICT, data mining, technology governance, responsible research and innovation, Habermas, information ethics, virtue ethics, hermeneutics, bioethics, computer ethics, epistemology)
- Professor David Steinsaltz, Department of Statistics (demography, ageing, genomics, stochastic modelling, longitudinal data)
- Professor Donna Kurtz, Oxford e-Research Centre, Department of Engineering Science (Digital technologies, linked data, global heritage applications)
- Professor Gesine Reinert, Department of Statistics (Statistical analysis of networks, models for networks)
- Prof Gina Neff (Social impact of AI, innovation, work, organisations, culture, theory, qualitative methods, critical data studies, Science and Technology Studies)
- Dr Grant Blank (Inequality, attitudes, political opinion formation, digital divides, social networks, social media, trust, privacy, journalism, inequality, political participation, mobile, security)
- Prof Greg Taylor (Economic theory, economic modelling, game theory, information economics, competition policy, regulation, markets)
- Prof Helen Margetts (Digital government, public management, public policy, collective action, political participation, democracy, political science, data science, experiments)
- Dr Janet B. Pierrehumbert, Oxford e-Research Centre, Department of Engineering Science (natural language processing, text mining, social networks)
- Professor John Coleman, Faculty of Linguistics, Philology, and Phonetics (speech, language)
- Dr Jonathan Bright (digital politics, democracy, smart cities, digital government, news media, online harms)
- Dr Joss Wright (Computational social science, network measurement. Machine learning, anomaly detection, Bayesian inference. Freedom of expression, internet censorship, internet shutdowns, surveillance. Conservation, illegal wildlife trade. Privacy enhancing technologies, data anonymisation.)
- Dr Kathryn Eccles (Digital humanities, crowdsourcing, cultural heritage, arts and cultural industries, education, impact, users, well-being, digital history, history, gender, sexism)
- Prof Luciano Floridi (Philosophy, activism, big data, censorship, cultural industries, power, ethics, governance, inequality, innovation, open data, privacy, security, social media, surveillance, trust)
- Prof Mark Graham (Big data, crowdsourcing, cultural industries, digital divides, ICT4D, inequality, innovation, open data, public policy, social media, labour, markets, digital labour, geography, transparency, participation, Africa, economic geography, production network, ethical consumption, power)
- Professor Michael Osborne, Department of Engineering Science (machine learning, future of work, AI and creativity)
- Professor Min Chen, Oxford e-Research Centre, Department of Engineering Science (data visualisation, data analysis, empirical studies, social science methodologies in visualisation, theories of visualisation)
- Dr Peaks Krafft (Participatory action research, artificial intelligence, cognitive science, critical data studies, science and technology studies, digital institutions)
- Dr Pieter Francois, Department of Anthropology and Museum Ethnography (digital humanities, historical and archaeological big data, text mining, ritual and religion)
- Prof Phil Howard (Political communication, international affairs, civic engagement, internet of things, computational propaganda, comparative methods, social media)
- Prof Ralph Schroeder (Big data, e-research, virtual environments, digital media, right-wing populism)
- Prof Rebecca Eynon (Datafication, inequality, learning, sociology of education, youth)
- Dr Renaud Lambiotte, Mathematical Institute (network science, dynamics on networks, urban systems)
- Dr Rosaria Taddeo (Ethics, Data Ethics, Ethics and AI, Ethics of Cyber Conflicts, Cyber Defence, Privacy, Trust, Surveillance, Security, Big Data, Open Data, Governance, Power, Hacktivism)
- Prof Sandra Wachter (Data Ethics; Big Data; AI; machine learning; algorithms; robotics; privacy; data protection-, IP- and technology law; fairness, algorithmic bias)
- Dr Scott Hale (Human behaviour, human factors, multilingualism, user experience, data science, computational social science, mobilisation, collective action, political participation, information visualisation, natural language processing, bilingualism, data mining, knowledge discovery, social network analysis, social media, social networks)
- Dr Taha Yasseri (Behaviour, big data, collective action, computational social science, crowdsourcing, political participation, social media, social networks, online dating, social intelligence, social network analysis)
- Professor Varun Kanade, Department of Computer Science (machine learning, algorithms, social networks)
- Prof Victoria Nash (Internet regulation and governance, content regulation, children’s online safety and well-being, technology policy, civic engagement, political theory)
- Prof Viktor Mayer-Schönberger (Big data, governance, law)
- Prof Vili Lehdonvirta (digital marketplaces, e-commerce, platform business, app stores, games, virtual currencies, crowdsourcing, online freelancing, volunteer work, ‘the gig economy’, and labour movements; especially from sociological, organisation studies, and science and technology studies (STS) perspectives)
- Dr Xiaowen Dong, Department of Engineering Science (social influence, human dynamics, urban computing)
Our induction programme is usually held in the first week of October, the week preceding the start of Michaelmas Term (also referred to as 0th week). During Induction Week students will be formally introduced to the OII’s Director, Director of Graduate Studies, Programme Directors, Graduate Studies Support team, as well as our faculty and administrative team. In addition students will be offered a full tour of the OII’s facilities and introduced to IT and library resources, followed by several informative DPhil induction sessions. There is also ample opportunity to get to know fellow students and staff through student-led social activities and an afternoon drinks reception. During October the Social Sciences Division also holds a welcome event for all new research students.
Our doctoral students are provided with working space in the department. We are equipped with advanced video conferencing facilities and high-speed network access. The OII’s library specialises in the social sciences, technology and computing, and our students also have access to the Bodleian Libraries, the University’s main research library.
Opportunities for teaching and training
We provide opportunities for DPhil students to gain teaching experience through mentored assistantship roles in some of the MSc courses. Students will have the opportunity to attend the ‘Introduction to Learning and Teaching at Oxford’ programme run by The Social Sciences Division, an interactive and discursive course in which attendees will explore common teaching formats (lectures, small groups, tutorials) and common experiences (for example, group management, preparation, presentation and delivery). Students must complete this programme if they wish to undertake a teaching assistant position at the Oxford Internet Institute. The OII also has a dedicated Teaching Assistant Coordinator who arranges in-house training.
Pastoral and Welfare Support
In addition to the pastoral support provided your college, as a department the OII seeks to support students by various means. Each degree programme has dedicated administrative support and the administrators in question will be able to help and advise students on a range of matters relating to their studies, or point them towards dedicated sources of support elsewhere in the University. Supervisors and the Director of Graduate Studies can also serve as a source of support, in addition to our dedicated Disability Contact and several Harassment Officers who can assist with connecting students with the appropriate support.
The DPhil in Social Data Science is designed as a natural continuation of the MSc Social Data Science and offers the opportunity for students to go deeper into a research topic of their choice.
Applicants to the MSc in Social Data Science programme who plan to continue on to the DPhil programme at the completion of the MSc are encouraged to apply for both programmes as part of their application by selecting the MSc+DPhil (1+3) Social Data Science when they apply. Continuation to the DPhil portion of the combined MSc+DPhil programme will require that students meet the normal DPhil admissions requirements and any conditions set to progress to the DPhil in Social Data Science.
Students admitted only for the MSc in their first year may also later apply to continue on to the DPhil, as may students from other universities who can demonstrate similar preparation at Master’s level. Students admitted to the 1+3 programme will be considered for funding for the duration of both degrees.
Details of fees, living expenses, and definitions of home and overseas students, together with information about potential sources of funding are available from the University’s Fees and Funding website.
There are a number of sources of funding for postgraduate students at Oxford. Details of all scholarships for which candidates may be eligible can be found on the University’s Fees and Funding website. To be considered for any of these scholarships both full- and part-time applicants MUST apply by the January deadline. The scholarships are all highly competitive and are awarded on academic merit.
Clarendon is one of the biggest of the University’s scholarship schemes, offering around 140 new scholarships each year to academically outstanding graduates. Clarendon scholarships are competitive, prestigious and highly sought-after. As well as providing for fees and living costs Clarendon aims to enhance the Oxford experience by offering students the chance to form lasting social, academic and professional networks. Students can apply by completing the funding sections of the graduate admissions form. As part of the admissions process, the Oxford Internet Institute Scholarship Committee will decide which applicants to nominate to the University for consideration. Further details of this scholarship can be found on the University’s Clarendon Scholarships page.
Economic and Social Research Council (ESRC) funding
The ESRC is the UK’s largest organisation for funding research on social and economic issues. The University, in collaboration with Brunel University and the Open University, hosts the Grand Union Doctoral Training Partnership (DTP) – one of fourteen Doctoral Training Partnerships accredited by the ESRC as part of a new Doctoral Training Network.
The Oxford Internet Institute’s graduate degree programmes are a recognised doctoral training pathway in the partnership and our Digital Social Science pathway is provided through two routes, MSc-to-DPhil (known as 1+3) and DPhil-only (known as +3), and is available to students studying part-time as well as those studying full-time. Applicants who wish to be considered for 1+3 funding must indicate in their application an interest in pursuing doctoral work and an interest in ESRC funding; applicants considered for the university competition for Grand Union DTP funding will be asked to submit a short research proposal.
In order to be considered for a Grand Union DTP ESRC studentship, you must select ‘ESRC Grand Union DTP Studentships in Social Sciences’ in the University of Oxford scholarships section of the University’s graduate application form. You must complete a Grand Union DTP Application Form and upload it, together with your graduate application form, by 12 noon on 10th January 2020 in order to be considered for nomination for the studentship.
Information about ESRC studentships at Oxford can be found on the Grand Union DTP website. Please ensure you have read all of the guidance available on the website before completing the ESRC Grand Union DTP Studentship Application Form. Questions can be directed to the Grand Union DTP Office.
All applicants must satisfy the ESRC’s citizenship and residence requirements.
Arts and Humanities Research Council (AHRC) funding
The AHRC provides public funding in support of research into the arts and humanities, for approximately one quarter of the UK’s research population. Oxford participates in the Open-Oxford-Cambridge AHRC Doctoral Training Partnership, providing a number of scholarships each year to students working in eligible subject areas across the Humanities and Social Sciences Divisions.
Information about applying for AHRC scholarships at Oxford can currently be found on the Open-Oxford-Cambridge Doctoral Partnership website. In order to be considered for a studentship you must apply by 12 noon on 10th January 2020 and tick the relevant box in the studentships section of the application form. You will also need to complete the OOC DTP Application Form and upload it as an additional document when completing your application.
OII Departmental Scholarship
The OII awards a limited number of DPhil Scholarships each academic year. These scholarships are open to both full- and part-time students (from any country) and all applicants who are offered a place on our programme are automatically considered for an award. Scholarships are awarded on the basis of merit.
How does the DPhil in Social Data Science differ from the DPhil in Information, Communication and the Social Sciences?
The DPhil in Social Data Science is designed for students with core quantitative skills who wish to develop their skills for analysing structured and unstructured data using advanced computational techniques such as machine learning. Theses in Social Data Science might develop new computational approaches for analysing human behavioural data and/or apply such approaches to answer a social science question. The DPhil in Information, Communication and the Social Sciences is designed for students interested in research about the Internet and related technologies and their societal implications. Theses in this programme might include quantitative, qualitative, computational or mixed methods applied to a broad range of questions about digital phenomena and could address questions about technology policy or practice.
Should I apply for the MSc or the DPhil in Social Data Science?
A substantial amount of training in our programmes happens at the MSc level. It is therefore expected that applicants to DPhil programmes already hold a taught masters or other advanced degree. For Social Data Science, applicants should examine the content covered in the MSc in Social Data Science and are advised to apply for the MSc if their current experience covers less than half of the content taught within the MSc programme. DPhil students will work with their supervisors and the Programme Director to identify any further areas of specialised training that is needed for their theses and opportunities to meet these needs from across the University. DPhil students will usually take the Foundation courses from the MSc Social Data Science programme unless they already have equivalent training.
When should I apply?
The full-time DPhil programme has two deadlines in November and January. consideration. The part-time DPhil programme has three deadlines in November, January and March. Applications submitted for all deadlines are given equal consideration, but both full-time and part-time applicants who wish to be considered for any scholarships should apply by the January deadline at the latest.
Please ensure that you start the online application process as early as you can, to ensure plenty of time to complete your application. Only applications that are complete by the deadline (including letters of reference) can be considered by the admissions team. All applications must be made through the University of Oxford Graduate Admissions site.
How do I choose a supervisor?
Our students are supervised by faculty from the OII and partner departments in the University. Please note that we will only admit students where appropriate supervision is available; please see the full list of faculty members eligible to supervise students on this programme. If having read these, you are still unsure who could supervise your proposed research (or if you are considering supervision by a faculty member from a different department within the University of Oxford) please contact us to discuss this at email@example.com.
Please note that it is strongly advised that DPhil applicants should contact a potential supervisor before they submit an application to check that there is appropriate supervision for their research proposal. Once DPhil applicants have identified an appropriate supervisor they should email them directly with a brief overview of the proposed research topic. The faculty member will then indicate whether they would be suitable to supervise the proposed topic.
What application materials do I need to submit?
The set of materials you should send with an application to the DPhil comprises: a statement of 1-2 pages and a research proposal of up to 2,500 words, in an area of research covered by at least one member of the supervisors; a CV/résumé; three references; official transcripts detailing your university-level qualifications and marks to date; one relevant academic essay or other writing sample from your most recent qualification of 2,000 words, or a 2,000-word extract of longer work.
Applicants who have not previously written on areas closely related to the proposed research topic may provide written work on any topic that best demonstrates their abilities.
Is the 2,000 word limit on the written work a minimum or maximum?
2,000 words is a maximum. Many students who find that their best work exceeds this length choose to submit a 2,000-word extract from that longer piece of work. We recommend that your chosen piece: demonstrates your capacity for independent or original thought; is systematically analytical rather than purely descriptive; addresses a clear question or problem; where relevant, draws on data or literature sources to support its main arguments; expresses its arguments with clarity and precision.
If I need to submit English Language Test results, when are they due?
Applicants who need to fulfil an English Language requirement will be informed of the deadline upon receiving their offer. Please note that if you have taken a test previously, it must be within 2 years of making your application for the results to remain valid, otherwise you will need to retake the test. Applicants are required to provide evidence of proficiency in English at the higher level required at the University.
Where can I find out about scholarships?
Please see the University’s Fees and Funding website for details of all scholarships for which you may be eligible.
How many of my references have to be academic? Can I submit references that are not academic?
Of the three required references, at least one should be academic. You are welcome to submit professional references, as long as they are able to comment on your academic potential.
What do I do about references if I have been out of academia for a few years?
The OII actively encourages applications from those with valuable experience in the private and public sectors and those who have interrupted their studies for other reasons. We judge every application in a holistic manner on its individual merits and the main role of the admissions process is to assess candidates’ academic potential and intellectual suitability for graduate study. With this in mind, mid-career applicants are encouraged to select or produce written work that demonstrates their ability for independent analytical thought. Non-academic referees are encouraged to comment, in particular, on candidates’ intellectual capacity and analytical skills.
Do you offer any online or part-time courses?
We do not currently offer any of our courses online. We do, however, offer the DPhil on a part-time basis. The part time DPhil is substantively identical to the full-time degree, but distributes the workload over five to six years for those who must fit study around work, family, or other outside commitments.
What fees do I have to pay?
Course fees cover your teaching, and other academic services and facilities provided to support your studies. They do not cover your accommodation or other living costs. You may have seen separate figures in the past for tuition fees and college fees. We have now combined these into a single figure.
See the University’s guidance on fee status and fee liability for information on Home/EU/Overseas student classification. As well as covering University and College fees, students will also have to support their maintenance costs. As Oxford is a relatively expensive place to live, it is recommended that students consult the University’s guidance on living costs when planning their budget, to cover accommodation, meals and other living expenses.
Why do I need to choose a college?
Oxford is a collegiate university: students and teaching staff belong both to a department and to a college. Colleges typically provide library and IT facilities, accommodation, welfare support, and sports and social events. Graduate students also benefit from the Middle Common Room (MCR) in their college – both a physical space and an organisation, it provides social events, advice, and a link to the graduate community. Your college will have a Tutor for Graduates or Senior Tutor whose role includes general oversight of all graduate members of the college, although your academic studies will be directed by your department or faculty. Each graduate student has a college adviser, a senior member of the college’s staff who will be able to offer support and advice. Further information is available on choosing a College on the University website, and from college prospectuses.
How do I decide on which college to choose?
We can’t advise applicants on their choice of college, however, all teaching is organised within the department so college choice will not make any significant difference to the way that students are taught or supervised. When making your choice, first check which colleges accept applications from OII students, then check the individual college websites. Factors you should consider when making your choice include; location, accommodation quality (and your eligibility for this), library facilities, any financial support the college may be able to offer (e.g. awards, bursaries or scholarships) and the collegiate atmosphere. Note that some colleges accept only graduate students or mature students. If you select a particular college as a preference it does not mean that you will be automatically offered a place there.
If I am accepted on a programme, am I guaranteed a place at a college?
Yes: Once you have received an offer from the department, your application will go forward for consideration by your preferred college, or the Graduate Admissions and Funding team will assign you a college for consideration if you have not selected a college preference. In the event of heavy over-subscription of a particular college, you may be allocated a place at another college. Colleges will contact candidates separately with their offer, subject to satisfaction of any funding conditions. A college decision can take 8-10 weeks following the departmental decision. The University does not guarantee accommodation at a college for its graduate students. However, many colleges do attempt to provide accommodation for graduate students during their first year of study, particularly in the case of international students. If your college is unable to provide any accommodation or the type of accommodation you need, you can contact the University Accommodation Office for further information and assistance.
I’m an international student!
The University of Oxford has a long tradition of welcoming international students, who currently constitute around 64% of all graduate students. We recommend that you consult the University’s International Office, which provides information to support international applications, such as on visas and immigration, scholarships and funding, US Graduate Student Loans, English Language requirements, Orientation Programmes, etc. EU students may also wish to consult the University’s page on the implications of the EU referendum.
What provisions are there for students with disabilities?
The University of Oxford is committed to providing equality of opportunity and improving access for all people with disabilities who work and study at the University. The University Disability Office has information about the support offered to help those with a disability maintain their track record of academic success as they pursue their studies. The ground floor of the OII is wheelchair-accessible, providing access to the library, seminar room, student common room and disabled toilet. The OII also has a disability contact and several Harassment Officers who can assist with connecting students with the appropriate support.
What facilities does the OII offer its students?
Our doctoral students are provided with working space in the department. We are equipped with advanced video conferencing facilities and high-speed network access. Our library specialises in the social sciences, technology and computing, and our students also have access to the Bodleian Library, the University’s main research library. Students are encouraged to engage fully in the intellectual life of the department, e.g. through participation in DPhil workshops, departmental seminars, and research projects.
Do I have to live in Oxford during my studies?
Full-time students are required by the University’s regulations to be in residence in Oxford during term time. That means a commitment to be in Oxford for at least the full nine weeks of all three terms of each academic year. You also need to be available in Oxford for several events outside full term, from the induction programme to examinations. Research away from Oxford should be discussed with your supervisor. Part-time students are not required to live in Oxford, but are expected to be present in Oxford on average 30 days per year. Please see the DPhil handbook for more details.
Do you offer any intensive, online or distance-learning courses?
We do not currently offer any of our MSc or DPhil programmes in an intensive, online, or distance-learning modality. Although we do make use of virtual learning environments and various other online components of study, both full and part-time students are required to attend in person during term time due to the collaborative and multi-disciplinary nature of our programmes, and the principles that underpin Oxford education as a collegiate university. We strongly believe that the face-to-face element of the programme is vital in providing a multi-disciplinary peer network for students to engage in ideas, discussion and debate.
We do, however, offer this programme on a part-time basis. The part-time DPhil is substantively identical to the full-time degree, but distributes the workload over five to six years for those who must fit study around work, family, or other outside commitments.
What does the schedule look like for a part-time DPhil student?
Part-time students can typically expect to spend at least 30 days physically in Oxford each year, and will be expected to commit approximately 20 hours per week to their studies. Part-time DPhil students will be expected to take core courses in Michaelmas Term of Years 1 and 2. These courses have been scheduled to allow part-time students to take them on a single day, so students will need to be able to attend classes in Oxford one day a week for the eight consecutive weeks of Michaelmas Term, as a minimum. In addition, part-time students will need to be present in Oxford in their first year for the full Induction Week (normally held the first week of October).
There are provisions to attend DPhil seminars and supervision meetings via video conference, the latter at your supervisor’s discretion, particularly from Year 3 onwards. However, classes for the core courses and any corresponding examinations in Michaelmas Term of Years 1 and 2 can only be attended in person.
Full-time: 3-4 Years
Part-time: 6-8 Years
12 noon UK time (midday) on:
Friday 15 November 2019;
Friday 10 January 2020;
Tuesday 3 March 2020 (part-time applicants only)
Course Director: Professor Balazs Vedres
DPhil Coordinator: Laura Maynard