A postdoc position, for up to 3 years, is available for an outstanding and ambitious computational/theoretical physicist or chemist to undertake research in the field of force field design. By its novel architecture the in-house force field FFLUX aims to make a step change in the reliability of modelling of peptides/proteins in aqueous solution.

The machine learning method Gaussian Process Regression is used to create knowledgeable quantum atoms that accurately predict energies and multipole moments. FFLUX combines accurate electrostatics and polarisation with an original treatment of short-range interaction and dispersion. The molecular dynamics program DL_FFLUX (derived from DL_POLY) enables geometry optimisation and simulation. 

The overall task is to further the development of FFLUX by extending, modifying, testing and perfecting in-house software. By using the concept of atomic transferability FFLUX will be able to make predictions for systems larger than those it has been trained for by machine learning.

The post is tenable from 1st August 2022.

Full details and how to apply:

https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=22352

Vacancy: SAE-018916

Closing Date: 14^th June 2022

Based within the Department of Chemistry at the University of Manchester, you will work with Professor Popelier and his team. The Department is ranked 3rd in Great Britain and 5th in Europe by the 2021 Nature Index.​​​​​​

You should have a PhD in computational/theoretical physics or chemistry, with at least 2 out the following 3 areas of expertise: electronic structure theory, molecular simulation or machine learning. Expertise in programming is essential. You should be capable of working under your own initiative and in a research team. Therefore, excellent communication and organisational skills are also required.