Postdoctoral Research Associate in the Mathematical and Computational Foundations of Artificial Intelligence

We invite applications for four Postdoctoral Research Associates (PDRA) to join the EPSRC Hub on the Mathematical and Computational Foundations of Artificial Intelligence. One PDRA will be recruited for each of the following four research themes: Learning with Structured & Geometric Models, Low Effective-dimensional Learning Models, Implicit Regularization, and Reinforcement Learning through Stochastic Control. 

A brief description of each these is as follows (additional details are in the further particulars):

Learning with Structured and Geometric Models. We will apply tools from manifold learning and Riemannian optimisation to leverage the underlying manifold structure for better training and novel network designs.

Low Effective-dimensional Learning Models. We will extend foundational theory of how large ML systems can be regularised to have dramatically fewer trainable parameters without sacrificing accuracy by analysing the use of low-dimensional building blocks

Implicit Regularization. We aim to develop mathematical understanding of implicit regularisation properties in deep neural networks to guide the development of algorithmic paradigms aimed at combining statistical optimality with computational efficiency.

Reinforcement Learning through Stochastic Control. We will develop methods from stochastic control, which will provide a mathematically grounded approach that has a well-posed continuous-time limit (as opposed to traditional RL methods that are inherently discrete and do not scale favourably for high frequency observations without judicious hyper-parameter tuning).

The PDRAs will work with faculty across the multi-university Hub, but will be employed by and directly supervised by faculty within the Mathematical Institute at the University of Oxford. Faculty within the Mathematical Institute associated with the above work packages include Profs. Cartis, Cohen, Hauser, Lambiotte, Reisinger, Sirignano, and Tanner.

These are two-year, fixed-term position, funded by a research grant from the EPSRC. The starting date of this position is flexible with an earliest start date of 01 March 2025. 

The successful candidates will be expected to conduct research which falls within the remit of this large-scale project and will have the opportunity to do so collaboratively with other members of the hub, both at Oxford and/or with hub partners which include universities as well as companies and governmental organisations.

They will contribute to the activities of the wider machine learning and data science research group and write up the results of their work, with co-authors, for publication in refereed journals and proceedings. There will be opportunities to contribute a small amount of teaching to the department, of at most three hours a week during the academic terms.

You will have, or be close to completing, a PhD in mathematics or a related discipline, and possess sufficient specialist knowledge in the discipline to work within established research programmes. Excellent communication skills are essential, including the ability to write for publication, present research proposals and results, and represent the research group at meetings.

We proudly hold a departmental Athena SWAN Silver Award and an institutional Race Equality Charter Bronze Award, which guide our progress towards advancing racial and gender equality. As part of our strategic aim to improve staff equality and diversity, we would particularly welcome applications from women and BME candidates, who are currently under-represented in positions of this type within the department.

Please direct informal enquiries to the Recruitment Coordinator (email: recruitment@maths.ox.ac.uk), quoting vacancy reference 176180.

Applicants will be selected for interview purely based on their ability to satisfy the selection criteria as outlined in full in the job description. You will be required to upload a statement setting out how you meet the selection criteria, a curriculum vitae including full list of publications, a statement of research interests, and the contact details of two referees as part of your online application. (NOTE: Applicants are responsible for contacting their referees and making sure that their letters are received by the closing date).

Applications received before 12.00 noon UK time on Monday, 02 December 2024 will receive full consideration. Applications after this date will be considered at the discretion of the committee.

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