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administrative duties, including some duties of a superior. You are expected to apply for and gain external funding not only to do your own research at the station but also to help develop the station and its
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Foundation Health Model. As a PhD candidate, you will conduct deep-dive research into training pipelines and reasoning techniques for clinical foundation models. You will join an elite, interdisciplinary team
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use machine learning and data science to find better ways to utilize this data in healthcare planning, personalized medicine and targeted recall-studies. In this position, you will be a part of an
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. Project overview Healthcare systems collect vast amounts of heterogeneous data routinely through interactions with individuals. Our mission is to use machine learning and data science to find better ways
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at the Department of Technical Physics. The aim of the project is to develop and validate image reconstruction methods and hardware for low-field (~50 mT) magnetic resonance imaging. As our new Postdoctoral
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, or innovation studies). This requirement must be met by beginning of the employment. Has demonstrated expertise in qualitative methods, preferably in qualitative comparative analysis Has a solid track record and
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health records. Medical Reasoning and Grounding: Developing advanced post-training and alignment techniques (RLHF, DPO, GRPO) to ensure foundation health models reason accurately and safely. Agentic
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on lymph node lymphatic endothelial cells, fibroblasts, and resident myeloid cells. Our long-term goal is to develop novel approaches for locally modulating immune responses within specific lymph nodes
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computational approaches to uncover mechanisms underlying complex diseases and to develop predictive, clinically actionable models. The successful candidate will work in a highly collaborative environment with
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of a highly experienced and enthusiastic research team and Unit, with whom you can share and develop your expertise Career development and learning opportunities in a multidisciplinary, international