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procedures. The project brings together cardiovascular imaging, generative AI, and computational modeling to develop probabilistic digital twins of coronary arteries. The goal is to create patient-specific
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remained unclear for decades, and thus design principles for discovering new thermal battery materials have been lacking. In this industrially sponsored PhD studentship, we have partnered with AWE fund a 3.5
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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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sufficiently robust, the experimental system may be progressively developed to explore more complex geometries, time-varying volume changes and increasingly physiologically representative cardiovascular models
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that looks plausible but violates physics and is therefore of limited use for grid planning. As a PhD candidate you will develop physics-informed, domain-constrained generative models for energy-system data
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will do Your degree programme will be the Applied Mathematics PhD. You will conduct mathematical modelling of formulated products, working with experimental data provided by industry partners. Examples
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AITHYRA GmbH - Research Institute for Biomedical Artificial Intelligence of the Austrian Academy of Sciences | Vienna, Virginia | United States | about 3 hours ago
Do you want to help transform human health through machine learning and life science approaches? Join AITHYRA in Vienna for a fully funded PhD at the intersection of machine learning, experimental
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Location: Central Cambridge We are seeking applications for a PhD position in AI in proteomics as part of the Horizon Europe MSCA Doctoral Network, ProtAIomics. This brings together laboratories
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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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This PhD project will investigate partial differential equations arising from kinetic models, with a particular focus on variational methods. The research will explore how variational structures