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do medical VLMs compare to each other, what are the trade-offs between model size / accuracy / utility / deploy ability etc Required knowledge Students with existing training in data science and AI
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data. Yet, their reliability remains a serious concern. This project aims to first explore current techniques such as fine-tuning, model alignment, prompt engineering and Retrieval Augmented
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do medical VLMs compare to each other, what are the trade-offs between model size / accuracy / utility / deploy ability etc Required knowledge Students with existing training in data science and AI
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climate physics and Earth System analyses, targeted climate model experiments, advanced statistics, including machine-learning- and explainable AI, to deliver usable climate risk estimates under current and
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knowledge-based reasoning. The goal is to move beyond isolated prediction models towards an integrated agentic system that can model patient trajectories, compare treatment strategies and generate
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features of the spectrum usage, interference, and exposure radiation footprints and the usage of these data in a realistic digital twin model that is able to mimic the radio environment and adapt
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have recently been developed in the Roke lab and used to image in real time interfacial water and electrostatic potentials on membrane interfaces of model membranes and in living cells. We will use
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, each robot experiences different environments, sensor calibrations and operating conditions. These distribution shifts and mismatches in system information can quietly erode model performance and
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. Areas of particular interest include: foundation model training, evaluation, and adaptation agentic workflows, tool-using models, and AI systems bespoke scientific applications of AI/ML, including in
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. Andreas Stohl, is part of the Department of Meteorology and Geophysics. The group develops the Lagrangian transport model FLEXPART and studies all aspects of transport in the atmosphere, ranging from