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.

Closing Date: 14th 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.

Full details (Vacancy: SAE-018916) and how to apply: 
https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=22352

Closing Date: 14th June 2022