Research Associate in Mathematics

Birmingham, United Kingdom
£33,199 to £39,609 per annum
Feb 06, 2019
Mar 06, 2019
Contract Type
Full Time
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 failure containment in 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 as well as 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 .

Informal enquiries should be directed to Professor David Saad: D.Saad .
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