How to Apply

  • Postdoc applicants:
      22 May 2024 Update: We are looking for two Postdocs to join OATML, working on Foundational AI Safety. You’ll lead and contribute to projects aimed at developing principled and practical safe AI methods which could be used in real systems. Check out linked roles here and here - closing date 12th June, 2024. Separate to these open roles, please note the funding opportunity with the Schmidt AI in Science Postdoctoral Fellowship Program.
    • PhD/DPhil applicants for Oxford:
        We are currently at capacity for PhD/DPhil students at the moment. When we are available to accept PhD students again in the future, it will be advertised here.

        About us: We are researchers with varied backgrounds, including Computer Science, Maths & Stats, Engineering, and Physics, who have worked in academia and industry in countries around the world.

        We work on topics such as developing Bayesian deep learning methodology, applications of ML, and understanding ML methodology. Examples include developing tools for robust ML, generative models, and methods to estimate uncertainty. This leads to lots of fun collaborations in the group between people working on applications and people working on methodology (in both directions).

        In addition to our collaborations within the group, we often work with other labs, e.g. in computational genomics (Debbie Marks at Harvard Medical School), autonomous driving (Toyota researchers), climate and earth observations (ESA), astronomy (Chris Lintott at Oxford Astrophysics), AI for good, and more.

        OATML has an open and friendly environment with regular academic and social gatherings. As an incoming student you will be paired with a current group member, who will be your buddy to help you navigate starting your PhD. All incoming students begin with a startup project to get a good grasp on fundamentals. This will give you the opportunity to find new interesting research questions by yourself. Then we will develop these questions into your own project which you will lead and develop.

        Applicants should have a Master's in a related field and a strong motivation and a sense of curiosity. If you are interested in joining us, please take a look at the papers we've put online to get a better sense of our work and whether it fits with your interests.

        Below is some information about the admissions procedure. Please feel free to email us with any questions about the group, but please email Graduate Admissions Office if you have questions about qualifications or the PhD admissions procedure. For the admissions procedure, more information can be found on the University website.

        PhD requirements:
        • Master's in Computer Science or a related field (or a four-year undergraduate degree)
        • Good communication and presentation skills in English
        • Knowledge and experience with the stuff you want to work on
        • Good mathematical or engineering background is preferred
        We recognize that there is a stigma around PhD prerequisites, and often applicants are discouraged as they feel underqualified. However, we would like to emphasize that only the first two points above are essential. If you're hesitant about your qualifications, please do reach out. Please don't hesitate to send any questions about course qualifications, pre-requisites, or questions such as 'is my undergraduate grade competitve enough?' to the Graduate Admissions Office.

        For questions about the group specifically, please email:
        Writing a research proposal for your PhD application:
        The most important thing in choosing a PhD is alignment between the lab you're applying to, and the research topics you are interested in. Your research proposal will be a core part of your application to a DPhil / PhD. I would suggest going over some our recent works here (papers with Yarin as last author; other papers are often external collaborations and not core lab research), or our blog posts here, and seeing if anything catches your eye. If so, I would encourage you to do some background reading on that topic (e.g. reading the references in the background section in that paper). And trying to draft a research proposal based on related questions you think would be interesting to answer (talking about why a specific question you found is interesting and worth answering, and broadly how you would approach it).

        A general word of advice is that a good research question would be:
        • specific to the topic (i.e. avoid stuff like "how can we solve AI"),
        • measurable (how would we know that we managed to answer the question? e.g. if you want to improve autonomous driving safety in out-of-distribution, what metric would we use?), and
        • achievable (even though it might require a few years of work to answer!).
        This is not something that you need to commit to work on during your PhD, but more to give us an idea for what sort of stuff you find interesting. Looking forward to your proposal!
        Applying and Funding:
        Please follow the instructions on the admissions website. You can also apply to one of the fully funded scholarships provided by the Centres for Doctoral Training (CDT) to do a PhD with us, such as AIMS (to work on statistical ML or applied ML), or the Health Data Science CDT. Other funding opportunities are available here, and you may also be eligible for scholarship programmes such as the Rhodes Scholarship. Please make sure to apply to more than one funding opportunity as we don't have control over these or the CDT admissions. We may also have funding opportunities for specific projects which we can offer to successful candidates. However, please note that we can only accept direct PhDs in exceptional circumstances, and that you should apply through the main Oxford programmes (preferably one of the CDTs or Rhodes), naming Yarin as a potential supervisor.
        If you have any further questions about the group specifically, please feel free to contact us and ensure that you include the following information in your email:
        • previous education (grades, course and university) and research work that you've done (e.g. published papers),
        • relevant internships or industry experience,
        • topics of interest to you and how they fit with the lab's wider research interests (see above for advice on how to write a proposal)
        Lastly, please note that as the deadline to applications gets closer, we often recieve dozens of emails each day from prospective applicants, and do not have the capacity to reply to everyone (we also need to spend some time doing research!). Please do not think a lack of response to mean you shouldn't apply. If you have a broader query about the process (i.e. not a question about the group specifically), please email the Graduate Admissions Office instead of us: you will be far more likely to get a reply!
        We wish all candidates the best of luck in the application process.
    • Internships:
        We do not accept interns at the moment. If we do in the future, it will be advertised here.

    Are you looking to do a PhD in machine learning? Did you do a PhD in another field and want to do a postdoc in machine learning? Would you like to visit the group?

    How to apply


    We are located at
    Department of Computer Science, University of Oxford
    Wolfson Building
    Parks Road
    OX1 3QD
    Twitter: @OATML_Oxford
    Github: OATML