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algorithms to enable autonomous execution of surgical interventions. The research program will include a systematic investigation comparing this autonomous surgical paradigm against expert surgeons performing
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, computer science, architecture, and engineering to develop scalable, data-informed solutions in sustainable design, construction, and energy management. The Cluster aims to modernize—and ultimately revolutionize
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Center for Devices and Radiological Health (CDRH) | Southern Md Facility, Maryland | United States | about 9 hours ago
: The Artificial Intelligence Regulatory Science Program conducts regulatory science research ensuring safe and effective AI/ML-enabled medical devices across rapidly expanding healthcare applications including
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interactions from every perspective—molecular, microbe, and natural host. For more information about the Agricultural Research Service (ARS) Research Participation Program, please visit the Program Website
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University): Quantum Computation & Quantum Algorithms https://youngseok-kim1.github.io/ykim.github.io/ 3. RESEARCH AREAS [Condensed Matter Physics] - Quantum topology and geometry - Topological materials
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Details Title HMS - Postdoctoral Fellow in Biomedical Informatics School Harvard Medical School Department/Area Biomedical Informatics Position Description Postdoctoral Fellows in Computational
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 23 hours ago
/Education: Ph.D. in Industrial Engineering, Operations Research, Industrial and Systems Engineering, Computer Science, or a closely related quantitative discipline A strong experimental and theoretical
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-Informed Neural Networks (PINNs) and hybrid models that respect the physical laws governing the real-world system Applying Deep Reinforcement Learning (DRL) algorithms to optimize processes within simulation
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 9 hours ago
advanced in silico prediction algorithms, analyzing machine learning approaches for toxicity pattern recognition, and participating in developing standardized computational frameworks for regulatory
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees