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work on generative AI, scalable architectures for scientific prediction tasks, and other approaches that tightly couple ML methodology with scientific insight. To give a sense of the breadth of profiles
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recrystallization and control nucleation for biomedical applications in e.g. heart and kidney cryopreservation. Where to apply Website https://www.academictransfer.com/en/jobs/359905/phd-in-de-novo-design-of-ice-bi
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MRI measurements can be translated into meaningful input for predicting optimal sensor phase configurations and feedback control; Identify pathways towards the integration of domain knowledge about MRI
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analysis with appropriate software, and, in particular, describing complex systems by simple equations. You have a good command of spoken and written English at the C1 level. You like collaborating with
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systems increasingly provide personalized recommendations in domains such as nutrition and lifestyle. However, many recommender and prediction systems rely heavily on opaque machine learning techniques
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opportunity to work in a top-tier interdisciplinary setting. This is what you will do You will develop predictive computational models to capture the formation and heterogeneous structure of microthrombi, with
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use. Frequently, even higher resolutions do not capture dynamic drivers. This mismatch limits the utility of climate projections for predicting localized glacier change. This project aims to close
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an international MSCA network and help advance cutting‑edge research on motor control and functional neurological disorders. Contribute to innovative gait adaptation studies and grow within a vibrant
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of existing studies to promote the use of risk-informed decision frameworks, prediction models, AI applied to planetary protection. Tasks include: Support the creation of probabilistic models for planetary
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understand and predict the behaviour, health and biodiversity of animals. Together, the PhD candidates strive for a better understanding of the ‘digital physiology’ of animals: how behaviour, , pathogens