A postdoc position is available in the Warwick Centre for Predictive Modelling to work in the group of Dr James Kermode as part of the Horizon 2020 Novel Materials Discovery (NOMAD) Centre of Excellence. Key objectives are to extend the functionality of the NOMAD repository for classical molecular dynamics codes.

The job will address aspects of materials modelling related to data generation, curation and inference, particularly with the aim of developing useful “Big Data Analytics” protocols for structure and property prediction via machine learning algorithms. Specific objectives are (a) completing the force-field-specific metadata, following the scheme of the NOMAD meta-information; (b) writing parsers for a number of force-field-based codes.

Candidates must have a PhD in physics, chemistry, materials science or a related subject, experience with classical molecular dynamics using standard codes such as LAMMPS or GROMACS and strong scientific software development skills using C, Fortran or Python. Experience with machine learning and/or first principles simulation approaches such as density functional theory would be an advantage.

Please contact Dr Kermode for informal enquires, see his website for more details or apply here.

The position is available from 1 March 2017 for 12 months in the first instance and may be extendable subject to mutual agreement and available funding. The closing date for applications is 18 Jan 2017.