Job Description

BACKGROUND

Two postdoctoral positions, each for 3 years, are available through UKRI funding underwriting a European Research Council (ERC) Advanced Grant. This position is open to outstanding and ambitious computational scientists to work in molecular simulation progressing the in-house machine-learnt potential called FFLUX. One post (A) will focus on considerably speeding up the in-house code DL_FFLUX, written in FORTRAN90, and will carry out the simulations. The second post (B) will advance the machine learning behind the FFLUX potentials. By its novel architecture, the locally developed 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 atomic energies and multipole moments. It is vital that the two naturally complementary postdocs collaborate.

Overall Purpose of the Job

The overall task is to advance the accuracy and performance of the in-house machine learning force field FFLUX.

What you will get in return:

Fantastic market leading Pension scheme Excellent employee health and wellbeing services including an Employee Assistance Programme Exceptional starting annual leave entitlement, plus bank holidays Additional paid closure over the Christmas period Local and national discounts at a range of major retailers

As an equal opportunities employer we welcome applicants from all sections of the community regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.


Our University is positive about flexible working you can find out more here


Hybrid working arrangements may be considered.


Please be aware that due to the number of applications we are unfortunately not able to provide individual feedback on your application.


Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.


Any CV's submitted by a recruitment agency will be considered a gift.

Enquiries about the vacancy, shortlisting and interviews:

Name: Paul Popelier


Email: paul.popelier@manchester.ac.uk

General enquiries:

Email: People.recruitment@manchester.ac.uk

Technical support:

https://jobseekersupport.jobtrain.co.uk/support/home

This vacancy will close for applications at midnight on the closing date.

Please see the link below for the Further Particulars document which contains the person specification criteria.