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material parameters for crystal plasticity simulations from experimental data through inverse analysis to establish structure–property linkages based on numerical simulations and to transform them into AI
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results from numerical modelling of surface mass balance, firn compaction and ice flow dynamics identifying and quantifying processes of ice sheet change and ice mass balances developing stochastic
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 2 months ago
experiments and measuring reaction rates in beach sediments applying and developing numerical and empirical transport-reaction models publishing results in scientific journals and communicating them to non
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investigation. Your tasks and responsibilities Develop and validate cellular models of acute paralogue dysfunction in developmental contexts (e.g. degrons) Map binding dynamics of paralogue proteins through
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measurements in a team of experts on and in the pyramids and creating digital object models with numerical simulations, for example, using Salvus software or similar. Publication of research results and
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basic willingness to work experimentally with laboratory animals (preclinical mouse models) is required Very good knowledge of English, German is an asset (helpful for teaching) Organizational and team
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interest in the topics of Structural Health Monitoring (SHM), Building Information Modelling (BIM), numerical simulations and real-time monitoring systems with the use of sensor technology. Proficiency and
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AWI - Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research | Bremerhaven, Bremen | Germany | about 2 months ago
numerical and empirical transport-reaction models; publishing results in scientific journals and communicating them to non-experts in an accessible way. Your Profile A university degree (M.Sc. or diploma) in
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Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience-informed design
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phenomena such as the spread of misinformation or the formation of filter bubbles. For this, we rely on rigorous probabilistic methods to model and analyse the intrinsic complexities of these systems