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website: http://www.esa.int Field(s) of activity/research for the traineeship Under the coordination of the Vega-E Liquid Propulsion Module Product Manager, in support of current developments of the Vega-E
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opportunities: https://go.fzj.de/LeadershipCulture In a large research institution like ours, science and administration work hand in hand. Our leadership model ( https://go.fzj.de/leadershipmodel ) provides
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/data from neuroscience to develop new AI solutions. This might include investigation in connection with neuroimaging, computational models of cognition, genetics, or other related areas. The position is
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reactive transport models. Synthesize results in presentations at conferences and journal articles. Where to apply Website https://seuelectronica.upc.edu/en/procedures/call-for-recruitment-of-research-s
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) Knowledge of surrogate modeling, GNNs or Physics-Informed ML Experience with academic writing or contributions to scientific papers High level of independence, motivation, and a structured, reliable work
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diagnosis, and therapy of diseases like cardiovascular diseases or cancer. Overall, the institute strives to advance precision medicine by combining knowledge from different fields such as biology, chemistry
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modelling, BIM and embodied carbon/lifecycle assessment for built environment applications is preferred. Knowledge in EN 15978 or similar standards for carbon assessment or lifecycle analysis. Prior
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related to staff position within a Research Infrastructure? No Offer Description Understanding and modeling material behaviour is central to many engineering challenges. This fully funded Doctoral student
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Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau | Landau in der Pfalz, Rheinland Pfalz | Germany | 16 days ago
with recognized expertise in environmental modeling/ environmental data science. We therefore welcome applications that complement our existing portfolio in an integrative manner. The successful
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Your Job: Chromatography modeling, while crucial for modern bipporcess development, still heavily relies on empirical determination of key model parameters. By combining protein structure