Research Associate/ Fellow in Computational Materials Discovery for Lasers (fixed term)
This is a theoretical/computational postdoctoral position for the prediction and development of novel optoelectronic materials, in particular new perovskite phases for super-radiant solid state lasers.
Project activities include the development of hierarchical computational materials discovery schemes combining machine learning, atomistic, and density functional theory (DFT) calculations to accurately and rapidly screen new perovskite phases, based on their stability and desired optoelectronic properties.
The candidate will develop and apply machine learning tools and algorithms to create a map of stable perovskite compounds with properties relevant to strong optical coherence and super-radiant emission. The candidate will then perform electronic structure calculations to investigate the effect of materials properties such as Rashba splitting on emission, before selecting target materials for synthesis.
This position is part of a European consortium aimed at transforming coherent light generation by developing sustainable super-radiant solid state lasers based on non-critical raw materials. Selected materials will be targeted for synthesis and device fabrication by our experimental partners.
Candidates should hold a PhD (or be close to completion) in materials science, chemistry, physics or similar.
The post is offered on a fixed-term contract until 31st August 2025 with the possibility for extension. The position can begin from September 2024. Hours of work are full time (36.25 hours per week). Job share arrangements may be considered. The position is based in the School of Chemistry, University of Nottingham in the group of Dr Katherine Inzani.
Please include a CV and cover letter in your application detailing your fit to the criteria in the role profile.
Informal enquiries may be addressed to Katherine Inzani katherine.inzani1@nottingham.ac.uk Please note that applications sent directly to this email address will not be accepted.
Further details:
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