Postdoctoral Research Assistant

University of Oxford
Oxford
5 months ago
Applications closed

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Postdoctoral Research Assistant in Machine Learning

Research Scientist, Quantum Chemistry and Machine Learning, London London

Research Scientist (Machine Learning), London London

Department of Physics, Clarendon Laboratory, Parks Road, Oxford Applications are invited for a Postdoctoral Research Assistant in Computational Plasma Physics. The post is available initially for a fixed-term duration until 31 August 2026. The focus of this project is to develop novel spectroscopic techniques in high energy density physics, such as resonant inelastic x-ray scattering (RIXS), and field them in experiments at large-scale x-ray free-electron laser (XFEL) facilities. Using these techniques, we aim to measure directly the electronic structure of extreme states of matter, and understand how it evolves under material compression and phase transformation. Recently published related work can be found here: Resonant inelastic x-ray scattering in warm-dense Fe compounds beyond the SASE FEL resolution limit - Communications Physics The successful candidate will work within the wider research group and lead our efforts on the theoretical and computational aspects of the project, including running and developing predictive simulations (atomic kinetics, density functional theory, molecular dynamics, etc.) and deploying modern data analysis approaches leveraging various aspects of machine learning and differentiable programming. The candidate will endeavour to connect these theoretical and computational results with the experimental measurements obtained within the wider research group and collaboration. The post-holder will have the opportunity to teach. Applicants should hold a PhD, or be close to completion, in physics or a related field, and have a strong background in computational plasma physics or more general electronic structure techniques. Previous experience in the computational modelling of x-ray interactions with matter at high densities 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 well within a larger international research environment.

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