|£36,024 to £44,263 per annum with the potential to under-fill at Grade 6 with salaries in the range of £32,332 - £38,205 p.a.
|30th November 2023
|22nd January 2024
Contract: Fixed term for 2 years
We are looking for a motivated Research Associate on Optimisation for Game Theory and Machine Learning. Reporting to Professor Paul Goldberg, you will be a member of a research group with responsibility for carrying out research for a small project having one other postdoctoral researcher.
The research methodology is mathematical analysis of algorithms, sometimes supported by computational experiment. Our general interest is in understanding the efficacy of algorithms that work by using local optimisation, in the context of various problems arising in applications. The post holder may provide guidance or collaboration with other members of the research group including research assistants, PhD students, and/or project volunteers.
You will carry out academic research and manage relevant administrative activities such as small scale project management, co-ordination of multiple aspects of work to meet deadlines. You will be expected to collaborate in the preparation of research publications, and book chapters, and contribute ideas for new research projects.
You must hold a PhD (or be close to completion) in related discipline, together with relevant experience. You should have previous experience of contributing to publications/presentations
The closing date for applications is 12 noon on 22nd of January 2024. Interviews are expected to be held in February 2024.
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 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.
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