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may play in stress responses, below-ground processes and pollination. The research combines controlled experiments, advanced measurement and multiphysics modelling, and will generate open datasets and
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, and catalytic processes. The project will use molecular dynamics simulations to understand molecular mechanisms of metal-based antimicrobial systems and biomolecular interactions, supporting the design
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Researchers (ECRs) have completed or are close to completion of their PhD, potentially waiting for their final viva voce examination, which must be passed prior to taking up the award. ECRs will not have held a
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application of innovative Machine Learning (ML) frameworks to understand and predict the global hydrological cycle. The role will require bridging the gap between process-based physical modeling and scalable
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systems, biomolecular interfaces, and catalytic processes. The project will use molecular dynamics simulations to understand molecular mechanisms of metal-based antimicrobial systems and biomolecular
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present your work at international conferences About you A PhD* or equivalent qualification/experience in Computer Science, NLP, AI, or a related field. Strong experience in natural language processing
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travel. Publish findings in high-impact journals and present at international conferences. Requirements: PhD or equivalent qualifications and experience in Analytical Chemistry, Chemical Engineering
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partners, particularly with the University of Oxford. The successful candidate will have a PhD or equivalent professional qualification and experience in a relevant physical/engineering
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in the planning and execution of in situ fieldwork, which includes travel. Publish findings in high-impact journals and present at international conferences. Requirements: PhD or equivalent
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System Models) to isolate and evaluate the role of individual processes. You will also assess how climate variability and extremes, including changes in the probability of high-impact events, are altered