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relevant to TCR prediction, including machine learning, molecular docking, and related modelling strategies. Experience in systematic literature review and the integration of computational findings with
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Biology, Department of Life Sciences, to develop intelligent systems that integrate metabolic modeling, omics analysis, and automated literature mining. About us The Department of Life Sciences conducts
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of these subjects are valued: machine learning, automatic control, system identification, optimization, signal processing, filtering and smoothing, probabilistic modelling, dynamical systems
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longer-lasting charging strategy for Li-ion cells using two complementary approaches. (1) By testing commercial cells under various controllable stress factors and integrating lifetime prediction models
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regression to represent unknown dynamics for model predictive control. Despite the practical success, there are still many theoretical open questions regarding scalability, uncertainty bounds and deriving
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Gaussian process regression to represent unknown dynamics for model predictive control. Despite the practical success, there are still many theoretical open questions regarding scalability, uncertainty
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The Department of Medical Biosciences is offering a postdoctoral scholarship within the project “Developing computational tools for large-scale human intracellular signaling models”. The scholarship
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signaling models”. The scholarship is full-time for 2 years, with access starting in May 2026 or by agreement. The research will be carried out in the laboratory of Cemal Erdem at the Department of Medical
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research in data-driven nutrition, health, and food science. With large-scale diet and health data, omics data, biomarkers, digital food and health services, we establish predictive models for evaluation
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. We use advanced computational technologies to discover how biomolecules and organisms function and interact. We pioneer new methods for prediction, prevention, diagnostics and treatment of diseases. In