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Field
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directions that can seed future independent positions. Work Performed Depending on candidate interests and expertise, projects may involve: Analysis of global dietary patterns using genomic approaches
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goal of informing public health policy. The postdoctoral scholar will have the opportunity to lead high impact research in infectious disease epidemiology and modeling across multiple pathogens. The work
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; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine
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tariff scheme (TV-L Brandenburg), salary group E 13. The full-time position for the Postdoc has a weekly working time of 40 hours (100%). It can also be filled on a part-time basis. The position will be
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Postdoctoral Researcher as a Junior Research Group Leader (m/f/d) - Research on and Implementation o
). The Empirical research should capture and analyze teaching and learning processes, for example by video analysis or eye-tracking. Development activities for instance may include AI tools, the creation
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. Proficiency in frameworks like Pyomo and/or TensorFlow/Pytorch/Keras Solid foundation in mathematics/statistics, with experience in cyber-physical systems modeling. Ability to work both independently and
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Part Time Full Time Anticipated Recruitment Range. Salary offered may be outside of this range as impacted by budget, UNC salary administration, and/or candidate qualifications. $61,000 - $61,008
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medical machine learning for a talented postdoctoral researcher (f/m/d) to deepen their expertise and interest in machine learning for medical image analysis and build their early scientific career. About
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-driven methods for structural analysis under multiphysics loading”. Expected start date and duration of employment This is a 4–year position from September 1st, 2025, or as soon possible. Job description
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the performance and scalability of large-scale molecular dynamics simulations (e.g. LAMMPS) using machine-learned potentials (e.g. MACE) through algorithmic improvements, code parallelization, performance analysis