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Leibniz-Institut für Astrophysik Potsdam (AIP) | about 2 months ago
duration be extended? No Work Arrangement In-Person In-Person Location(s) Potsdam Germany Job Description We invite applications for doctoral student positions in Computational Astrophysics for
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fidelity. Particular emphasis will be placed on integrating data-driven modelling with physics-informed deep learning to improve computational efficiency while maintaining physical realism and predictive
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in another way. Strong interest in theoretical ecology, ecological networks, response diversity, ecosystem stability, and mathematical and computational modelling. Experience with scientific
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Computational modelling of the emergence of somatosensory cortical maps School of Psychology PhD Research Project Self Funded Dr Hannes Saal , Dr SP Wilson Application Deadline: Applications
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how people perceive, move and make decisions in complex and uncertain environments? Do you enjoy combining experimental research with computational modelling to tackle fundamental questions about human
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pharmacology (anaesthetics, psychedelics) or brain stimulation, primarily in macaques, emphasising cross-species comparison and whole-brain computational modelling. Training/supervision You will gain skills in
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computational systems modelling approaches to investigate road accident causation and safety in existing and future road transport systems. This is an exciting opportunity to develop and lead research
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computational chemistry or a related discipline and experience in the molecular modelling of polymers, polysaccharides, and preferably cellulose. Informal enquiries are welcome and should be made to
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» BiochemistryPharmacological sciences » PharmacyComputer science » 3 D modelling Years of Research Experience 1 - 4 Additional Information Website for additional job details https://science.phd.uj.edu.pl
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in working with nuclear fuel modelling