AI Research Group Project Support Officer
| Dyddiad hysbysebu: | 18 Gorffennaf 2025 |
|---|---|
| Cyflog: | £34,982 i £40,855 bob blwyddyn, pro rata |
| Oriau: | Rhan Amser |
| Dyddiad cau: | 17 Awst 2025 |
| Lleoliad: | Oxford, Oxfordshire |
| Gweithio o bell: | Hybrid - gweithio o bell hyd at 1 diwrnod yr wythnos |
| Cwmni: | University of Oxford, Dept of Computer Science |
| Math o swydd: | Cytundeb |
| Cyfeirnod swydd: | 180911 |
Crynodeb
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 administrative and project support to the PI and research group. This will include day-to-day administrative tasks such as diary, email, and group expense management, booking meetings, arranging events, data collection and report generation, maintaining details regarding group research outputs and website maintenance.
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 is offered with part-time hours (15 hrs/week). This role is hybrid.
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 29th August 2025. Interviews are likely to take place in September.
In this role you will provide administrative and project support to the PI and research group. This will include day-to-day administrative tasks such as diary, email, and group expense management, booking meetings, arranging events, data collection and report generation, maintaining details regarding group research outputs and website maintenance.
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 is offered with part-time hours (15 hrs/week). This role is hybrid.
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 29th August 2025. Interviews are likely to take place in September.