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experience with computational modelling, method development, and numerical analysis applied to biology (or allied fields like neuroscience and medicine) the ability to work effectively in a multi-disciplinary
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Associate with mathematical modelling and numerical/data analysis background to join our food system resilience project, led by University of Reading, joining a large interdisciplinary team with an excellent
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mathematical and numerical tools? Are you an innovative and productive team player who enjoys working in an interdisciplinary team with a background ranging from mathematics and theoretical physics all the way
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. The research will involve both analytical work and numerical computations. The balance between analytical and numerical type work is flexible and can depend on the preferences and skills of the successful
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’ (PHOENIX), led by Associate Professor Thomas Aubry (University of Oxford). Using a combination of laboratory experiments, field work and numerical modelling, PHOENIX aims to improve our understanding
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the research team around Univ.-Prof. Dr. Philipp Grohs. Our ideal candidate has a strong interest in Applied Mathematics, possesses solid and profound background knowledge in Numerical Analysis, Approximation
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level of detail extracted from these experiments. As part of this role, you will work closely with other researchers to translate these experimental results into our numerical models, helping to improve
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, advanced imaging techniques and numerical modelling. About the role A successful candidate will be working on the EPSRC funded project New perspectives in photocatalysis and near-surface chemistry: catalysis
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good understanding of the relevant basic theory, skills in data analysis and numerical modelling, and a strong research track record. Please direct enquiries about the role to: Only applications received
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. We are a highly international and research-oriented Department. More than 30 full-time junior and senior professors together with numerous PhD students form an international community dedicated