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Description Mission: Perform the characterization and simulation of CO2 capture and reuse processes. Functions to be developed: Characterize, simulate and model processes for capturing, purifying and reusing
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. Are you interested in tackling these challenges with cutting-edge AI sensing techniques? At the AISensing team we focus on AI-powered sensing technology, spanning large-scale AI models, simulation of next
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the Heat and Fire Lab (https://heatandfire.github.io/ ) in the Department of Engineering at King’s College London. About the role We are looking to appoint a full-time (1.0 FTE) Research Associate to work
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of mathematical derivations — checking proofs, running numerical simulations, implementing models in Python or Mathematica, researching the relevant literature. You do not need to be an expert in all areas the QBF
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contributions in one or more of the following key areas: computational modeling of chemical systems, AI-driven materials discovery/design, robotics for chemical synthesis, machine learning applications in
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disease progression, care transitions, and quality of life. You will develop and refine a health-economic R-based simulation model, integrating surrogate outcomes from psychosocial and technology-based
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-informed models simulating system behaviour and providing decision-relevant insights Translating methods into decision-support prototypes and case studies in collaboration with academic and industrial
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Assistant to support applied research at the intersection of healthcare, artificial intelligence, and data analysis The primary focus of this role will be large language model (LLMs) and other machine
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); j.wen@surrey.ac.uk . Information about research activities at FMEG can be found here: https://www.surrey.ac.uk/fire-and-explosion-modelling-group
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interests, the project may take a more theoretical direction (e.g., focusing on continuous-time modeling, semiparametric theory and efficiency) or a more applied and computational direction (e.g., focusing