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agent-based modeling combined with Large Language Models to create context-sensitive governance frameworks that address different developmental stages of CCs. Your role: You'll conduct three in-depth case
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Monte Carlo methods for glassy dynamics and complex materials Supervisor: Dr Michael Faulkner, University of Warwick Glasses are materials that combine macroscopic solid behaviour with amorphous liquid
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combines flow and materials chemistry, characterisation, and reaction optimisation. You will gain skills in synthetic co-ordination chemistry, advanced characterisation techniques, machine learning and
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exotic crystalline structures that remain poorly understood despite extensive experimental investigations. This project combines cutting-edge sampling techniques with developing machine-learned potentials
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. The PhD student will develop, apply, and combine theoretical molecular dynamics (MD) simulations with experimental techniques such as X-ray diffraction (XRD) to characterize, at the molecular level
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to conventional feed and food production. The project combines anaerobic and aerobic biotechnologies to capture carbon and produce new forms of protein with near complete carbon capture for a climate
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molecular mechanisms where genetic mutation, exposure to high insulin and low glucose combine to cause neurodegeneration in the brain. You will employ multiomic deep phenotyping to identify molecular
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barrier in the planned KBS-3 concept for final disposal of spent nuclear fuel. The PhD student will develop, apply, and combine theoretical molecular dynamics (MD) simulations with experimental techniques
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patterns across multiple annotation types. The core aim is to generate new scientific insight by associating LCRs with their functions through a combination of expert curation and modern machine learning
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barrier in the planned KBS-3 concept for final disposal of spent nuclear fuel. The PhD student will develop, apply, and combine theoretical molecular dynamics (MD) simulations with experimental techniques