Postdoctoral Research Assistant in Model Selection

We are looking for a highly motivated researcher with a documented track
record of successful research projects and a desire to do interdisciplinary
research. This postdoctoral position will focus on Bayesian approaches to
uncertainty in electrophysiology models, the selection of these models, and
optimal experimental design for these tasks. The research will be carried out
under the supervision of Dr Gary Mirams as part of a Wellcome Trust and Royal
Society funded fellowship project entitled “Improving assessment of drug-
induced cardiac risk with mathematical electrophysiology models”, and
Professor David Gavaghan under an EPSRC Cross Disciplinary Interfaces
Programme (www.2020science.net).

You will have a doctorate or equivalent degree in a relevant discipline, have
evidence of independent research, and have experience in the area of
statistical modelling of complex systems. Additionally, you will have a keen
interest in the application of mathematical and statistical models to
biological data and an eagerness to learn about the modelling approaches used
in electrophysiology. Excellent programming and statistical skills are
essential, and you will be expected to produce leading scientific research and
publish results in scientific journals.

This post is fixed-term for up to 3 years.

The closing date for applications is 12.00 noon on 29 July 2015.