Job Description

The Oxford Applied and Theoretical Machine Learning group at the Department of Computer Science has a new opening for a Project Support Officer, working together with Professor Yarin Gal.

In this role you will provide project and administrative support to the PI and research group. This will include day-to-day tasks such as diary and email management, data collection and report generation, maintaining details regarding group research outputs, website maintenance, booking meetings, and arranging events.
These tasks will be in support of research focused on AI model safety, security, reliability and robustness, as well as foundational research on frontier models. This covers topics such as uncertainty quantification and reliable decision-making, multi-agent systems, reasoning, neural network quantisation, on-device machine learning, and benchmark development.

About the research group.

Machine learning (ML), or "AI" as it is referred to by the media, has been the driving force behind the most exciting recent technological advances, having its impact on fields as diverse as medical imaging, conversational agents, astronomy, and many more. The Oxford Applied and Theoretical Machine Learning (OATML) group is an energetic world-leading research group working at the core of machine learning research and its applications, located at the Computer Science department, and led by Yarin Gal, Associate Professor of Machine Learning. We are a multidisciplinary team of researchers (post-doc scientists and DPhil students), coming from diverse backgrounds including Computer Science, Maths & Stats, Engineering and Physics.

About Us

The University of Oxford is a stimulating work environment, which enjoys an international reputation as a world-class centre of excellence. Our research plays a key role in tackling many global challenges, from reducing our carbon emissions to developing vaccines during a pandemic.

The Department of Computer Science at Oxford is renowned for pioneering research and teaching across diverse fields, consistently ranking among the best in the world. Our commitment to innovation drives us to tackle complex technological and societal challenges.

What We Offer

As an employer, we genuinely care about our employees' wellbeing and this is reflected in the range of benefits that we offer including:

An excellent contributory pension scheme

38 days annual leave

A comprehensive range of childcare services

Family leave schemes

Cycle loan scheme

Discounted bus travel and Season Ticket travel loans

Membership to a variety of social and sports clubs


This role offers a flexibility of hybrid working, requiring a minimum of 1-2 days per week on-site.

Diversity

Committed to equality and valuing diversity.

Application Process

You will be required to upload a supporting statement, CV and the details of two referees as part of your online application.

The closing date for applications is midday on 3rd June 2025. Interviews will take place in June.