Postdoctoral Research Assistant in Computational Physics

Applications are invited for a Postdoctoral Research Assistant in Computational Physics.

The post is available initially for a fixed-term duration of 12 months. The project is focused on using deep learning to encode the exchange and  correlation functionals within a fully differentiable density functional theory framework. The objective is to develop a physics-based deep learning approach to quantum modelling of strongly-correlated systems that can approach chemical accuracy, is highly transferable to novel systems, and can be used in the study of matter in extreme conditions. See our recent paper for more technical details about the approach: https://arxiv.org/abs/2102.04229. 

The successful candidate will work within the wider research group on developing deep learning approaches for accurately modelling the xc potential, and will support the development of our differentiable density functional theory simulation suite. The candidate will validate the model by comparing to other approaches available in the literature, and will be expected to publish their progress in scientific journals and present their work in national and international conferences.

The post-holder will have the opportunity to teach. Applicants should hold a PhD, or be close to completion, in physics, computer science, or a related field, and have a solid background in condensed matter physics.

Previous experience in the field of density functional theory, theoretical or computational quantum modelling of condensed matter systems, or in deep learning, will be an advantage.

Candidates are expected to demonstrate the ability to work independently on cutting edge research projects, to communicate their research, objectives, and interests effectively, and to work effectively within a larger international research environment.

Please direct enquiries about the role to Sam Vinko. ([email protected])

Only applications received before midday (UK time) Thursday 5 August 2021 can be considered. You will be required to upload a statement of research interests, CV and details of two referees as part of your online application.