Teaching Assistants
These opportunities are open to current DPhil students at the University of Oxford in the first instance.
For each position, the gross salary will be £21.35 per hour (equivalent to Grade 6 point 7 on the University scale) before Tax and National Insurance deductions, if applicable.
How to Apply
To apply please send your CV and cover letter to msc@oii.ox.ac.uk by noon on Monday 10 August 2026.
You should also include a brief email of support from your supervisor or Director of Graduate Studies confirming that they are happy for you to undertake this TA work whilst completing your DPhil studies.
The cover letter should include:
* Please note a valid right to work in the UK will be required for this role. Under the 2006 Immigration, Nationality and Asylum Act the University has a duty to prevent illegal working by carrying out document checks to confirm that a person has the right to work in the UK. All employees, casual workers and Tier 5 sponsored visa holders must have their right to work checked either online or in person (depending on the immigration status) before they can start.
Two TAs are required to support Dr Fabian Stephany in teaching the core course, Digital Social Research Methods: Methods Core, taken by all students on the MSc Social Science of the Internet in Weeks 1-8 of Michaelmas Term.
The lectures run on Mondays, 13.30pm – 15.30pm.
The TA sessions run on:
The expected hours are up to 15 hours per week per TA (Weeks 0 – 8), for a maximum of 135 hours.
Based on a role at a maximum of 15 hours per week, a typical week will involve:
Two TAs are required to support Dr Fabian Braesemann in teaching the core course, Digital Social Research Methods: Statistics Core, taken by all students on the MSc Social Science of the Internet in Weeks 1-8 of Michaelmas Term.
The lectures run on Thursdays, 9.15am – 11.15am.
The TA sessions run on Thursdays, 11.30am – 13.45pm.
The expected hours are up to 15 hours per week per TA (Weeks Minus 1 – 9), for a maximum of 165 hours. Hours are flexible depending on TA capacity and do not need to be split equally, e.g. the role could be split 30/70 instead of 50/50. If you are available for more than or fewer than 15 hours per week, please specify this in your application.
The major requirements for the TAs are to answer student questions during weekly TA sessions and to mark student assignments. Since this is an introductory course, the job does not require advanced statistical skills. Rather, the course focuses on concepts (up to and including linear regression analysis), meaning the ability to clearly explain basic concepts is most important.
The TAs should support the convenor in assembling and preparing further study materials for the students and hold an introductory tutorial in Week 0.
One or two TAs are required to support Prof. Ralph Schroeder in teaching the core course, Internet and Society, taken by all students on the MSc Social Science of the Internet in Weeks 1-8 of Michaelmas Term.
The lectures run on Mondays, 9.30am – 11.30am.
The TA sessions run on:
The expected hours are up to 20 hours per week for one TA or 12 hours per week for a joint post (Weeks 0 – 9), for a maximum of 200 hours (single post) or 120 hours (joint post).
A typical week will require at minimum attendance and assistance at the course lecture (2 hours on Mondays Wk 1-8), plus holding four weekly student drop-in support sessions (Mondays and Tuesdays wk 1-8). In addition, the TAs are expected to respond to student questions via email and on the Canvas course page.
The TAs shall also provide assistance in organising, invigilating, and providing feedback on the course formative (timed exam) and revision sessions. The TAs shall also have short organisational meetings with the convenor.
Please specify in your application whether you are interested in (i) the single 20-hour appointment; (ii) one of the joint 12-hour appointments, or (iii) either.
One or two TAs are required to support Prof. Sandra Wachter in teaching the core course, Internet Technologies and Regulation, taken by all students on the MSc Social Science of the Internet in Weeks 1-8 of Michaelmas Term.
The lectures run on Thursdays, 14.00pm – 16.00pm.
The TA sessions run on:
The expected hours are up to 16 hours per week for one TA or 8 hours per week for a joint post (Weeks 0 – 8), for a maximum of 144 hours (single post) or 72 hours (joint post).
The TA(s) will carry out preparation for tutorials, actively lead two hours per week of open seminar exercises and group debates, mark formative assessments, and other duties. Knowledge of the landscape of internet regulation, the technologies underlying the internet and emergent technologies (e.g. AI, generative AI, facial recognition software etc) would be highly beneficial.
While some of the work can be done remotely (e.g. prep and marking), the TAs are required to support in-person during the lecture (Thursdays) and carry out the tutorials in person (Thursdays and Fridays).
Based on a job share between two TAs at a maximum of 8 hours per week each, a typical week might involve:
Plus assistance with formative essay marking in Week 6, with a two-week expected turnaround.
Please specify in your application whether you are interested in (i) the single 16-hour appointment; (ii) one of the joint 8-hour appointments, or (iii) either.
One or two TAs are required to support Prof. Brent Mittelstadt in teaching the core course, Data and Society I, taken by all students on the Social Data Science in Weeks 1-8 of Michaelmas Term.
The lectures run on Tuesdays 14.00pm – 16.00pm.
The TA sessions run on:
The expected hours are up to 16 hours per week for one TA or 8 hours per week for a joint post (Weeks 1 – 8), for a maximum of 128 hours (single post) or 64 hours (joint post).
Some knowledge of foundational issues in social data science is required.
A typical week includes attending the lecture/seminar (two hours on Tuesdays) plus hosting one or both of two in-person office hours (on Thursdays). There will also be occasional organizational meetings with course convenors and leading or facilitating small group discussions during certain weeks.
Please specify in your application whether you are interested in (i) the single 16-hour appointment; (ii) one of the joint 8-hour appointments, or (iii) either.
Two TAs are required to support Dr. Bernie Hogan in teaching the core course, Fundamentals of Social Data Science in Python, taken by all students on the Social Data Science in Weeks 1-5 of Michaelmas Term.
The lectures run on Mondays, Wednesdays and Fridays 14.00pm – 15.15pm.
The TA sessions run on Mondays, Wednesdays and Fridays, 15.15pm – 17.00pm.
The expected hours are up to 10 hours per week per TA (Weeks 0 – 5), for a maximum of 60 hours each.
The successful candidate will be expected to assist students with their coding and server access during the tutorials as well as assisting in the marking of formative assessments. Week 0 will be used to practice the specific coding skills for the course as well as to develop ‘practice answers’ for the resulting lab sessions and plan division of labour as well as timelines.
The TAs must have excellent skills in data science with Python. This includes a familiarity with Jupyter notebooks, Pandas, univariate or bivariate information visualisation, and programmatic use of APIs. The course uses Visual Studio and GitHub. The position does not require extensive familiarity with machine learning or multivariate statistics. Experience with programming on a server will be an asset. Previous teaching experience is also an asset.
The TAs will be responsible for leading:
– One tutorial per week in weeks 1-5
– One dedicated session on Server access in week 0
– Drop-in hours for server help in weeks 2-5.
The TAs will be jointly responsible for:
– Brief written feedback to two assignments for Fundamentals
– Creation of example answers to formative assignments
The TAs will be expected to attend:
– Weekly planning meetings with the course convenor and the other TA
– Two-hour kick-off planning meeting in week 0
The TAs will be expected to complete as part of their work:
– The code material for the course in preparation for the course at least one week prior.
– A reading of the required course material.
– Oxford’s self-directed information security course certificate (https://www.infosec.ox.ac.uk/do-the-online-training).
– Other related coding tasks from the convenor as relevant for class material.
Two TAs are required to support Dr Chris Russell in teaching the core course, Machine Learning, taken by all students on the Social Data Science in Weeks 6-8 of Michaelmas Term.
The lectures run on Mondays, Wednesdays and Fridays, 14.00pm – 15.00pm.
The TA sessions run on Mondays, Wednesdays and Fridays, 15.00pm – 17.00pm.
The expected hours are up to 10 hours per week per TA (Weeks 6 – 9), for a maximum of 40 hours each.
The post holder is expected to give tutorials for the intensive machine learning module of the MSc in Social Data Science.
An ideal candidate has detailed knowledge of machine learning, to a level as covered in the course, both theoretical as well as practical. Many exercises covered in the tutorials involve hands on work with Python / jupyter notebooks, using modern libraries such as pandas, sklearn and pytorch. The candidate should be a fluent user of those libraries. Preferences is given to DPhil students and post-docs working on machine learning related topics and who ideally have previous tutoring experience.
One TA is required to support Dr Mohsen Mosleh in teaching the core course, Research Design for Social Data Science, taken by all students on the Social Data Science in Weeks 1-8 of Michaelmas Term.
The lectures run on Tuesdays, 09.45am – 11.45am.
The TA sessions run on Tuesdays, 12.00pm – 13.00pm.
The expected hours are up to 12 hours per week (Weeks Minus 1 – 8), for a maximum of 120 hours.
The prospective TA should have experience in social data science research design, and will ideally have some experience of/engagement with a range of quantitative and qualitative methods.
The TA is expected to:
(1) Be present at all lectures (two hours on Tuesdays) and to assist facilitating seminar discussion and related hands-on activities in class;
(2) Facilitate weekly drop-in sessions (one hour on Tuesdays) for students to help with assignments and general queries;
(3) Help students with general queries outside of class by email;
(4) Assist in the provision of feedback on formative coursework