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STARS and HSMA STARS is an Open Science project that aims to increase the quantity and quality of computer simulation models that are open for reuse by health researchers and the NHS. The post holder will
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- Develop original numerical methods for facility simulation in presence of expansion waves - Demonstrate improved estimates of rate constants for two-temperature models - Contribute
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be the state estimation of the robotic system from external cameras. Familiarity with existing methods from these domains, such as Deep Learning, Quality-Diversity algorithms, reinforcement learning
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analysis and machine learning methods for optimisation and decision making, to describe the F&V supply chains for various products at regional UK scale and assess their resilience to cascading risks
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, delivering tested methods, and creating algorithms to expand MMFM capabilities across domains like cardiology, geo-intelligence, and language communication. The postholder will help lead a project work package
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probabilistic ensemble techniques to improve uncertainty representation in climate simulations. Apply and validate Monte Carlo methods (e.g., importance sampling and other rare-event estimation methods
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. Ready to be part of our team? Let’s shape the future together! About the team: Our group develops and applies quantum mechanics-based methods for the description of condensed matter systems, including
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research methods (including research ethics, interviewing, and analysis using software programmes such as NVivo. Strong experience in community engagement (preferably with minoritised ethnic people
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buildings closed days for all full time staff (Part time workers should pro rata this by their FTE). Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm to see the
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application of Hamiltonian methods to gauge theories, though you will also be encouraged to develop and pursue your own research directions. Applicants should have a PhD in physics and a track record of