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Field
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several cancer research groups represented, including joint seminars and other collaborative activities. The group uses various data sources and modern techniques to improve predictive modelling, including
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 23 days ago
from the surface or the coast into the interior ocean Test Lagrangian tools and contribute to their development Conduct model simulations covering the recent decades and the future Present project
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years the atmospheric modeling community achieved major advances in its capability to numerically simulate iodine chemistry in the atmosphere. This project will take advantage of the 1D chemistry and
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field in hand by May 2026. Preferred Qualifications: Experience in Thermal Spray Materials/Processes/Characterization/Modeling. Experience in Solid Mechanics/Thermomechanics/Finite Element Analysis
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, and can analogous mechanisms be engineered into multi-agent AI systems? You would answer this question by building and testing computational models, developing multi-agent simulations where agents
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support research in: • Transportation systems modeling and simulation, including O/D modeling, multimodal network modeling, agent-based or behavioral modeling • Large-scale computing, cloud-native analytics
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Project: Enhancing APEX for simulating environmental and economic impacts of CAFO operations using the APEX model, funded by USDA-NRCS. Texas A&M AgriLife Research is seeking a highly motivated and
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, while accounting for dynamic and stochastic demand patterns. The project addresses these challenges through a combination of advanced optimization methods (e.g., flow-based models that strengthen
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genetics. ● Experience with protein biochemistry and functional assays. ● Experience with mouse infection models. Brief Description of Duties: The Postdoctoral Associate will assist the Principal
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recruiting an outstanding and ambitious postdoctoral researcher in computational biology to advance the integration and modeling of large-scale microscopy data using modern machine learning approaches