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, innovative technologies for biomass conversion, neural network systems, and artificial intelligence for more efficient mathematical and computational approaches. Subject description The work focuses on
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genetic analyses and generalised linear mixed-effects models, and ideally also in the use of some mathematical models (e.g. Integral Projection Models) Experience in data processing, statistical analysis
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, collaborating with leading experts in AI, mathematics, orthopaedics, and physiotherapy, with direct impact on patient care. About the research project This position is hosted in the Polster Lab at the Division
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, Department of Materials, ETH Zurich. Research environment The Division of Subatomic, High-Energy and Plasma Physics conducts research in theoretical and experimental subatomic physics, mathematical and high
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explainable AI models for personalized treatment planning in sports medicine and orthopaedics. You will work in a highly interdisciplinary environment, collaborating with leading experts in AI, mathematics
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into consideration. We are looking for candidates with a Ph.D. in Electrical Engineering or equivalent, a strong mathematical background and a strong publication record in journals relevant to the research field. As
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. Research environment The Division of Subatomic, High-Energy and Plasma Physics conducts research in theoretical and experimental subatomic physics, mathematical and high-energy physics, plasma and fusion
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/engineering, veterinary medicine, and often in cooperation with subject areas: architecture, work science, economics, mathematics, computer science, statistics, etc. For more information about the department
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Stockholm University, Department of Mathematics Position ID: 2543-PDAG [#26488] Position Title: Position Type: Postdoctoral Position Location: Stockholm, Stockholm 106 91, Sweden [map ] Subject Area
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Physics performs research on theoretical and experimental subatomic physics, mathematical and high-energy physics, plasma and fusion physics, as well as nuclear physics. This diversity of research topics