23 parallel-and-distributed-computing "Multiple" Postdoctoral positions at Virginia Tech
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Job Description The Department of Computer Science, the Department of Electrical and Computing Engineering, and the Innovation Campus at Virginia Tech will be jointly hosting a Postdoctoral
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software Preferred Qualifications • Experience in ecological modeling, population dynamics, or fisheries management • Familiarity with species distribution models, catch rate standardization, stock
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-based models, and remote sensing technologies. Required Qualifications • Ph.D. in Civil or Environmental Engineering, Hydrology, Data Science, Geosciences, Computer Science, or a related field. PhD must
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Construction Engineering, Civil Engineering, Mechanical Engineering, Computer Science, Robotics, or a related field. Ph.D. in relevant engineering degree. PhD must be awarded no more than four years prior
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and optimization of measurement-based quantum computing protocols for quantum simulation of quantum many-body models. Preference will be given to candidates familiar with the stabilizer formalism and
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. - Interest in mentoring graduate students and contributing to the strategic direction of a dynamic research program. Exempt: Not eligible for overtime Appointment Type Restricted Salary Information 53,550
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candidate will play a key role in developing and advancing new models and simulations for Computational Fluid Dynamics (CFD) hypersonic codes. Specific tasks include developing new turbulence and transition
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his PhD degree in Prof. Curtis Berlinguette’s lab at University of British Columbia in Canada in 2018. He then moved to Prof. Erwin Reisner’s lab at the University of Cambridge for postdoc program. In
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Job Description Dr. Shenglin Mei lab at the Fralin Biomedical Research Institute (FBRI) Cancer Research Center- DC is seeking highly motivated Computational Biology postdoctoral associate to join
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interdisciplinary team at the NSF COMPASS Center, which integrates tissue engineering, stem cells, materials, virology, computational biology, machine learning, molecular environmental engineering, science