Two postdoc positions are available in the Warwick Centre for Predictive Modelling within the School of Engineering at the University of Warwick to work in the group of Dr James Kermode.

(1) Enhancing the Novel Materials Discovery Laboratory for Classical Molecular Dynamics Codes

This position is associated with the Horizon 2020 Novel Materials Discovery (NOMAD) Centre of Excellence. The role 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.

(2) Predictive Modelling of the Fundamentals of Fracture in Metals

Key objectives of this EPSRC-funded project (EP/P002188/1) are to develop methodology that allows energy barriers for rare events to be computed with quantum mechanical precision in systems containing ~10⁶ atoms using a multiscale QM/MM framework, and to apply this new methodology to predict rates for activated materials failure processes in representative systems such as dislocation motion, crack growth, and crack tip dislocation emission in nickel, aluminium and tungsten. Relevant publications include Kermode et al., Phys. Rev. Lett 115, 135501 (2015) and Kermode et al., Nature, 455, 1224-1227 (2008).

Candidates for either postdoc positions must have a PhD in physics, chemistry, materials science or a related subject, experience with first principles methods at the level of density functional theory and/or classical molecular dynamics and strong scientific software development skills using C, Fortran or Python.

Please contact Dr Kermode ([email protected]) for informal enquires or see his website for more details.

Both positions are 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.