Postdoctoral Research Associate in Deep Learning

We are currently inviting applications for a Postdoctoral Research Associate
to work with Professor Justin Sirignano at the Mathematical Institute,
University of Oxford. This is a three-year, fixed-term position, funded by a
research grant from the Engineering and Physical Sciences Research Council
(EPSRC). The starting date of this position is flexible with an earliest start
date of 01 March 2024. We particularly welcome applications from individuals
who are able to start between 01 March and 01 October 2024.





The successful candidate will be part of a research group funded by a joint
NSF and EPSRC grant to the University of Oxford and the Boston University:
“DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine
Learning: Recurrent, Graphical, and Deep Neural Networks”. The research will
involve collaboration between the postdoctoral research associate, Prof.
Justin Sirignano (University of Oxford), and Prof. Konstantinos Spiliopoulos
(Boston University).





Neural network models in machine learning have achieved immense practical
success over the past decade, revolutionizing fields such as image, text, and
speech recognition. The training algorithms used for these complex machine
learning problems – although successful in practice – are often ad hoc.
Mathematical theory is yet to be established in many cases, and there is the
potential to improve training algorithms and models via rigorous mathematical
analysis.





The objective of this research project is to develop new mathematical theory
for the training algorithms and neural network models used in several key
areas of machine learning. Analysis will leverage methods from stochastic
analysis and weak convergence theory to study the asymptotics of online,
stochastic training algorithms and neural network models as the number of
hidden units becomes large. The research project is highly interdisciplinary,
integrating methods from probability, partial differential equations,
stochastic analysis, optimization, and machine learning.





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 at the email
address given below, quoting vacancy reference 168225.





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**
).





Only applications received before 12.00 noon UK time on Monday 04 December,
2023 can be considered.