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relocations services, please visit talent.arizona.edu Duties & Responsibilities Develop mathematical, computational, and/or control-theoretic models of recurrent neural dynamics, with particular emphasis on how
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therapeutic targets. Develops and applies machine learning and statistical modeling approaches for biomarker discovery, classification, prediction, and patient stratification. Develops algorithms and
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the design and operation of next-generation thermal systems, developing strategies to model, optimize, predict, and autonomously control thermal systems behavior in complex systems. The candidate will
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-boundary MHD surrogates) for real-time predictions and control-oriented execution (<1 ms execution time). Advanced Control Synthesis: Synthesize and computationally test model-based (Model Predictive Control
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project. The position will provide core expertise in physics-based environmental and ocean modeling, with emphasis on numerical simulation and prediction of ocean conditions such as currents, tides, waves
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Particle Control (PEPC) group of the Fusion Energy Division at Oak Ridge National Laboratory. The PEPC group performs experimental and modeling work, focused on the boundary region of tokamaks, stellarators
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National Aeronautics and Space Administration (NASA) | Merritt Island, Florida | United States | about 6 hours ago
physiological responses. By incorporating these imaging-derived traits into genomic prediction workflows, the participant will explore how high-throughput phenotyping strengthens selection models. While
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system integration A record of peer-reviewed publications Experience with AI/ML-based control, such as reinforcement learning, learned or model-predictive control, or vision-guided manipulation Experience
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oceanography, numerical modeling, acoustic propagation, and scientific computing. The postdoctoral researcher will develop, apply, evaluate, and integrate uncertainty modelling into the predictions
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system models and quantifying uncertainty in their predictions. Conduct fundamental research on the formulation of probabilistic system dynamics models, including knowledge integration, likelihood