Research Associate in Generative AI

The Department of Computer Science is looking to employ a Research Associate
to work within a research group, reporting to Prof Yarin Gal. The post holder
will be a member of the Oxford Applied and Theoretical Machine Learning
(OATML) research group with responsibility for leading research for projects
in Generative AI. Conducting original research, you will develop fundamental
methodologies and tools in the context of real-world Generative AI challenges.





As a Postdoctoral Researcher, you will lead and contribute to projects aimed
at developing principled and practical methods which could be used in real
systems. This research requires coping with challenges such as intractable
probabilistic inference and robustness. The project will involve both
theoretical work as well as empirical analysis on challenging tasks.





In addition to research, this role will also assist in providing day-to-day
supervision for DPhil students and research assistants, as well as support of
grant applications and ongoing grant progress reporting.





Project website is https://oatml.cs.ox.ac.uk





It is essential that successful candidate would hold a relevant PhD/DPhil or
being close to completion with post-qualification research experience.





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 12 noon on 17th March 2025.**
Interviews are expected to be held in March.





**We are a Stonewall Top 100 Employer, Living Wage, holding an Athena Swan
Bronze Award, HR excellence in Research and Race Equality Charter Bronze
Award.**





Our staff and students come from all over the world and we proudly promote a
friendly and inclusive culture. Diversity is positively encouraged, through
diversity groups and champions, for example
http://www.cs.ox.ac.uk/aboutus/women-cs-oxford/index.html , as well as a
number of family-friendly policies, such as the right to apply for flexible
working and support for staff returning from periods of extended absence, for
example shared parental leave.





Demonstrating a commitment to provide equality of opportunity, we would
particularly welcome applications from women and black and minority ethnic
applicants who are currently under-represented within the Computer Science
Department. All applicants will be judged on merit, according to the selection
criteria.