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. The project seeks to develop mathematical models for allocation of critical resources during pandemics. Populating these instances with real-world data we would then develop novel algorithms to solve them
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to integrate empirical data into predictive models. You will collaborate closely with experimentalists to tightly integrate hypothesis generation and validation. You will be expected to disseminate our work
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Collaborate on synthetic data modelling and NLP techniques to support safe, reusable research practices Support stakeholder engagement, training and product ownership across federated TREs Establish and nurture
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for assessments. Analyse and interpret data. Apply knowledge to advance new intellectual understanding. Disseminate findings through publications, seminars, and conferences. Supervise students and guide PhD
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for assessments. Analyse and interpret data. Apply knowledge to advance new intellectual understanding. Disseminate findings through publications, seminars, and conferences. Supervise students and guide PhD
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this will involve the development of novel ML/DL methods which leverage both computational and experimental data. Candidates should also have experience of numerical modelling (e.g. CFD and FEA), working as
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To join the Airway Innate Immunity Research group led by Prof Cliff Taggart at the Wellcome-Wolfson institute for Experimental Medicine. This MRC-funded position will involve the evaluation of a
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related to staff position within a Research Infrastructure? No Offer Description Background Applications are invited from graduates with a strong first degree and PhD in Psychology for a Research Fellow
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Specification PhD (or near to completion) in high energy particle physics Experience with operation and use of Roman pot-based near-beam spectrometers Experience with analysis of data from Roman pot-based near
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Qualifications: PhD awarded within 3 years in business administration, computer science, information systems, data science, biomedical engineering, or a related discipline. Programming & Data Skills: Strong