Research Associate in Mathematics
Engineering & Applied Science
Salary: £33,199 to £39,609 per annum
Grade: Grade 08
Contract Type: Fixed Term (3 years)
Basis: Full Time
Closing Date: 23.59 hours GMT on Thursday 15 November 2018
Interview Date: To be confirmed
We are looking for a highly motivated individual for this postdoctoral research position in the general areas of statistical physics, machine learning and Bayesian inference, and their application to optical communication networks. The emphasis of this research will be on developing and employing theoretical and numerical methods from Bayesian statistics, machine learning and statistical physics to optimise routing and containment strategies on optical networks as well as the inference and optimisation of operational parameters in single channels.
The successful candidate must have a PhD in a relevant discipline, e.g. Mathematics, theoretical Physics or related subject. You should have excellent mathematical and computational skills and have a background in statistical physics, Bayesian inference and machine learning. knowledge of optics/laser-based systems is an advantage. While the main thrust of the work will be carried out within SARI and with Professor Saad, the position is part of the multi-institutional EPSRC-funded programme grant TRANSNET; hence, a significant level of collaboration with the Aston Institute of Photonics Technologies, University College London and Cambridge University is expected.
Further details on the collaborative TRANSNET research project can be found on http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/R035342/1.
Informal enquiries should be directed to Professor David Saad: D.Saad @aston.ac.uk.