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scale over molding experiments with natural fiber materials Characterize fiber distribution, adhesion, mechanical properties, and barrier performance Develop and integrate simulation models for material
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drought early warning and monitoring system for large-scale river basins. The project will explore both data-driven and model-based approaches for drought predictions, paving the way for a continental high
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mathematical modelling and simulation. Partial differential equations will be applied to model drug distribution and partitioning in multiphase systems using the drug’s partition coefficient as a driving force
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the Center for Pharmaceutical Data Science Education (CPDSE) and will be conducted under the supervision of Associate Professor Casper Steinmann . The project concerns physics-based computational modeling
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– Adaptive & Agentic AI. The PhD project focuses on developing robust and reliable machine learning systems that can adapt at test time under real-world distribution shifts. Modern foundation models (e.g
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. The project will also delve into generation and integration of synthetic data, via deployment of numerical simulations with existing advanced calibrated multiphysics models, with real data acquired through
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Energy Modelling”. The PhD candidate will be supervised by supervisors from DTU and Chalmers. This project will integrate energy technology, building physics, HVAC systems, control systems architecture
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the limitations of current simulation methods by enhancing machine learning interatomic potentials and develop ML approaches to model rare events and complex environments. A key focus will be solving the "chicken