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Field
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companies. The research will integrate techniques of numerical analysis and structure-preserving algorithms to generative modeling in AI. It will build upon the work done at IMF and SINTEF in this field. We
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methods that extend current sets of flood scenarios derived from physical and numerical models, incorporate climate change effects, and then use these enriched datasets to assess the future insurability of
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30th September 2026 Languages English English English We are looking for a PhD candidate in Structure-preserving Generative Modeling Apply for this job See advertisement This is NTNU NTNU is a broad
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increasingly popular in recent years. The recent introduction of OpenAI’s ChatGPT made large-scale models available to the public, which enables the integration of AI in everyday objects and tasks. As a result
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? We are looking for a PhD candidate to develop AI methods that extend current sets of flood scenarios derived from physical and numerical models, incorporate climate change effects, and then use
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the following areas is considered a merit: nuclear fuel, fuel-performance modelling, reactor physics or nuclear engineering, numerical modelling of heat transfer, material behaviour or solid mechanics
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advanced experimental and modelling methods to better understand the behaviour of industrial lubricants under extreme operating conditions. Lubricants in gears, bearings and other mechanical systems can be
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, France to complete the project. Objectives The objective of this PhD project is to develop advanced numerical modelling tools to support the digital twins of refractory materials, with the aim
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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | about 2 months ago
models). Your tasks Development of analytical theories of biomolecular phase transitions, focusing on liquid-liquid phase separation. Development of numerical simulation tools, e.g., for process modeling
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tomography, high-pressure reactor) with numerical modelling (COMSOL) to quantify and predict dissolution. • Select and characterise biogenic shells (foraminifera, pteropods) from oceanographic cruises