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. The project seeks to advance population health using innovative quantitative methods in system dynamics computational modeling and structural equation modeling applied to accelerating the translation and
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ecosystem functioning. The postdoctoral project will focus on analyzing and modeling tree architecture in relation to forest vitality and stress predisposition. The work will combine 3D structural data (from
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are particularly interested in candidates with a strong mathematical background and expertise in one or more of the following areas: High-dimensional probability and concentration/functional inequalities Markov
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spectrometry-based metabolomics data, in part based on generative AI models of chemical structures. The position is available starting July 2025, and will remain open until excellent fits are found.The
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Ph.D. or equivalent degree in mathematics, physics, computer science, bioinformatics, or a related field Experience in developing deep learning models Ideally, prior experience in analyzing biological
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interpretation is subjective, heavily relying on clinician expertise. This project funded by the Hanarth fund combines ultrasound imaging with histopathology data to train advanced AI models for automatic tumor
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character. The Faculty of Science, Technology and Medicine (FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer
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Join our team as a Early-Career PostDoc (m/f/d) in the research area of AI‑based modelling full-time (39.2 hr/week), fixed term for two years. Leibniz-IWT stands for research in the field of new
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Postdoc: Geospatial AI Modelling & Uncertainty Quantification of Biomass Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 32 to 40 Application deadline
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understanding of non-stationary complex systems through theoretical analysis and numerical simulation develop efficient statistical algorithms for analyzing and inferring dynamical models from multivariate time