Postdoctoral Research Associate in Deep Learning

The successful candidate will join the Machine Learning & Data Science research group and conduct research on the mathematical theory of deep learning as part of the joint NSF-EPSRC project "DMS-EPSRC:
Asymptotic Analysis of Online Training Algorithms in Machine Learning:
Recurrent, Graphical, and Deep Neural Networks". The research will involve collaboration with Professor Justin Sirignano at Oxford and Professor Konstantinos Spiliopoulos at Boston University. The project develops new mathematical theory for training algorithms and neural network models, drawing on probability, partial differential equations, large deviations, stochastic analysis, optimisation and machine learning.
The successful candidate will contribute to the activities of the Machine Learning & Data Science research group, develop rigorous mathematical proofs for convergence and asymptotic analysis of deep learning models, methods and algorithms, and collaborate in the preparation of research publications. 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.
We proudly hold a departmental Athena SWAN Silver Award and an institutional Race Equality Charter Bronze Award.
We are currently inviting applications for a Postdoctoral Research Associate in Deep Learning to work with Professor Justin Sirignano at the Mathematical Institute, University of Oxford. This is a 6-month, fixed-term position funded by an EPSRC grant. We anticipate a starting date of 1 December 2026 (or as soon as possible thereafter) and an expected end date of 31 May 2027.

There is scope for flexibility in the start and end dates, subject to approval by the department and the funding agencies.