Project Title: Time for a Step Change in Force Field Design

Supervisor: Prof Popelier
Co-supervisor: Dr Bane

A Research Associate for 2 years, with possible extension of another 2 years, 
is available through UKRI funding underwriting a European Research Council (ERC) Advanced Grant. 
This position is open to an outstanding and ambitious computational scientist to work 
in molecular simulation with an eye on considerably speeding up codes 
written in Fortran.

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 [1].
The machine learning method Gaussian Process Regression [2] is used to create 
knowledgeable quantum atoms that accurately predict energies and multipole moments. 
FFLUX needs to benefit from fully optimised parallelisation of the in-house 
program DL_FFLUX [3] (derived from DL_POLY). 
You will use both OpenMP and MPI, port to GPUs and 
ultimately to Field Programmable Gate Arrays (FPGAs). 

[1] Application of quantum chemical topology force field FFLUX to condensed matter simulations: liquid water, 
B.C. Symons and P.L.A. Popelier, J.Chem.Theor.Comp., 18, 5577-5588 (2022). 
http://doi.org/10.1063/5.0095581

[2] FEREBUS: A High-Performance Modern Gaussian Process Regression Engine, 
M.J. Burn and P.L.A. Popelier, Digital Discovery, 2, 152-164 (2023).
http://doi.org/10.1039/d2dd00082b

[3] FFLUX: a parallel, Quantum Chemical Topology Force Field, 
B.C.B. Symons, M. K. Bane and P.L.A. Popelier, J.Chem.Theor.Comp., 17, 7043-7055 (2021). 
https://doi.org/10.1021/acs.jctc.1c00595


The post is tenable from 1st Sept 2023.

Full details on how to apply: 

https://www.jobs.manchester.ac.uk/displayjob.aspx?isPreview=Yes&jobid=24147&advert=external


Job reference (vacancy): SAE-020768

Deadline: 12th June 2023

Based within the Department of Chemistry at the University of Manchester, 
you will work with Prof Popelier (and his research group) and 
associated consultant computer scientist Dr Bane. 
The Department is ranked 3rd in Great Britain and 5th in Europe by the 2021 Nature Index.

You should have a PhD in computer science or in physical sciences 
but with experience in parallelisation and GPUs, ideally with some experience of FPGAs. 
Expertise in programming is essential. 

You should be capable of working by your own initiative 
while interacting effectively in a research team. 
Therefore, excellent communication and organisational skills are also required.