645 computer-programmer-"https:"-"UCL"-"https:"-"https:"-"https:"-"Dr" Postdoctoral positions in United States
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of Applied/Computational Mathematics. Research topics of interest include numerical methods for scientific machine learning and AI, and their applications to various science and engineering disciplines
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systems for accelerating computational catalysis and experimental design. The successful candidate will contribute to building AI-native frameworks that combine first-principles modeling, machine-learning
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-related duties as assigned. Minimum Qualifications MD or Ph.D. in Basic Science, Health Science, or a related field. No experience required. Preferred Qualifications Be able to plan and conduct experiments
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to 8 hours/day, lifting <30 lbs, may view computer up to 8 hours/day. Shift Generally Monday – Friday, 8a-5p with some flexibility Job Summary This position is designed to have 70% clinical time, 15
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) in the field of accelerator physics or a closely related science and engineering discipline Strong experience developing and applying computational modeling and simulation Familiarity with accelerator
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holding a PhD degree in Biomedical Sciences or a related field are eligible to apply. Life sciences (Biology, Genetics, Biochemistry, etc.) PhDs with computational experience are also eligible
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for Gravitation and the Cosmos and its Center for Multimessenger Astrophysics , as well as the Institute for Computational and Data Sciences and the Center for Astrostatics and Astroinformatics . Education and
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 1 hour ago
USNH Employees should apply within Workday through the Jobs Hub app The Global Ecology group at the Earth Systems Research Center, University of New Hampshire (UNH), has an immediate opening for a postdoctoral research associate. The goal of this project is to advance understanding of how...
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. Familiarity with computational modeling of structure-function relationship Experience in identifying metabolites in biological samples. Sufficient knowledge in statistical analysis tools (e.g., SAS, R, XLstat
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the doctoral degree prior to the start date of the appointment. Demonstrated interest and a clear career development plan in implementation science. Strong writing, analytic, and communication skills; experience