8th February 2018 : Postdoc – Machine learning and batteries – U. of Cambridge

Postdoctoral research associate: Machine learning and the physics of
battery degradation

We invite applications for a Postdoctoral Research Associate position in
the Department of Physics, University of Cambridge with Dr Alpha Lee's
research group. The position is funded for up to 36 months by the EPSRC
and this position can be taken up from 12th March 2018. This project is
a part of the Faraday Challenge fast start project on battery
degradation (a large consortium led by Professor Clare Grey between
Cambridge, Glasgow, UCL, Imperial, Liverpool, Manchester, Newcastle,
Southampton and Warwick with 25 investigators).

Dr Alpha Lee's group (www.alpha-lee.com ) aims
to design materials by combining physics with machine learning. Recent
research highlights include developing methods inspired by statistical
physics and random matrix theory to predict protein-ligand affinity,
inferring probabilistic models using a liquid state theory approach, and
deriving a scaling theory for the structure of battery and
supercapacitor electrolytes.

The post holder will elucidate physical mechanisms of battery
degradation by using machine learning algorithms to analyze large
experimental datasets. Those data include current-voltage-time
measurements, electrochemical impedance spectroscopy and other
characterization techniques. Those datasets will be bespoke generated as
part of the consortium. The project aims to arriving at a new paradigm
for improving battery performance.

To apply online for this vacancy and to view further information about
the role, please visit: http://www.jobs.cam.ac.uk/job/16206.