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. university groups within CMS. Our instrumentation expertise spans detector operations and upgrades (Level‑1 muon trigger, CSC muon system), tracking algorithm R&D, and future HL‑LHC trigger algorithm
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for the DOE Oak Ridge Environmental Management Science Education and Internship Program, you will need to meet the following eligibility criteria at the time of application: Have a cumulative GPA of 3.0 on a
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Sciences at Texas A&M University Texas A&M Forest Service Texas A&M Veterinary Medical Diagnostic Laboratory As the nation’s largest most comprehensive agriculture program, Texas A&M AgriLife brings together
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Engineering, Aerospace Engineering, or a related field. Degree must be conferred upon hire. Preferred Qualifications Applied expertise in optimal control, heuristic optimization, graph search algorithms, and
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algorithms, and machine learning to solve complex aerospace engineering challenges. Developed and implemented AI-driven solutions for autonomous lunar and asteroid landings, as well as cislunar operations
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Job Summary The research group of Prof. Ming Xie in the Physics Department at The University of Texas at Dallas invites applications for a postdoctoral position in theoretical and computational
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Postdoctoral Associate in the Department of Biomedical Informatics & Data Science (BIDS), Yale School of Medicine Job Description We seek full-time Postdoctoral Associates in the areas of highly
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 5 hours ago
experience programming in the Unix/Linux environment using Python, Java, C/C++, or Julia; must have experience with algorithms, numerical techniques, and computational methods, specifically for uncertainty
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computer science, operations research, applied math, statistics, or a related field Strong background in machine learning, optimization, and/or algorithm design Excellent written and verbal communication skills
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about exploring and applying new statistical, computational, or machine learning techniques to astronomical data sets, and extending current methodology to be applicable in the era of big data. Looking