Postdoctoral Research Associate in Machine Learning

2 months ago


Liverpool, United Kingdom University of Liverpool Full time

A Post-Doctoral Research Associate in Machine Learning for Organic Materials position is available within the £10 M Centre for Functional Materials Design, with the main focus to develop cutting edge computational methodologies with a primary focus in organic chemistry within the research group of Professor Andrew Cooper.

This post will suit an ambitious individual motivated to produce step-change advances in new materials by implementing new and existing computational methods. The top-level responsibilities, depending on your expertise, will be as follows:
**Machine learning**: direct experience in Bayesian (or other black-box) optimisation, deep learning, and/or reinforcement learning, applied to chemical data, experimental or computational.

**Molecular modelling**: adequate experience in (ab initio) molecular dynamics (MD) and, more desirably, MD augmented by machine/deep learning based interatomic potentials.

**Computational chemistry**: in-depth knowledge and extensive experience in electronic-structure calculations, particularly applied to predict molecular or solid-state materials properties.

Any applicants who are still awaiting their PhD to be awarded should be aware that if successful, they will be appointed at grade 6, spine point 30. Upon written confirmation that they have been successful in being awarded their PhD, they will be moved onto grade 7, spine point 31 from the date of their award.

To be considered for this post, you should include a cover letter that clearly sets out both your skills and your career motivation plus a one-page research statement that outlines your ideas for activity that would add to our existing programme and theme.

The post is available as a fixed term 3-year contract.



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