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reinforcement learning for edge-cloud-based computation. In both cases, vehicles and robots must be able to navigate around obstacles and manage safety constraints along the planned trajectory, even in situations
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, further information can be found at http://ki.se/en/meb We welcome applications for up to two full-time postdoctoral researchers to join our multi-disciplinary team focused on precision medicine in cardio
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demonstrations in optimization and simulation; quantum information theory; and hybrid quantum-classical algorithms. We particularly encourage candidates whose research transcends traditional boundaries between
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for robots and autonomous vehicles. Design and optimization of control and trajectory planning. Experience in functions similar to those described will be valued, specifically in the development of research
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treatment optimization. Leveraging the Human Phenotype Project’s longitudinal cohort data—from in-depth clinical assessments to continuous monitoring of lifestyle and health indicators—faculty in
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insurance, generous paid leave and retirement programs. To learn more about USC benefits, access the "Working at USC" section on the Applicant Portal at https://uscjobs.sc.edu. Position Description Advertised
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by animal models that optimize for single causes or treatments, without reflecting the diversity and complexity seen in patients. This Marie Skłodowska-Curie Actions (MSCA) doctoral network PhD project
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Lexington, KY Grade Level 08 Salary Range $19.00-30.09/hour Type of Position Staff Position Time Status Full-Time Required Education LPN Click here for more information about equivalencies: https://hr.uky.edu
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
computational tools to enable practitioners to solve problems in statistical and probabilistic analysis, modeling, optimization, and the evaluation of system performance. The faculty engage in fundamental
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on diffusion and/or flow matching, that can rapidly adapt pre-trained models to new tasks and select optimally informative simulations at each stage in a design process. Collaborate closely with PhD students