31 parallel-and-distributed-computing research jobs at Virginia Tech in United-States
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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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. Experience with both experimental and computational approaches is desirable, as is proficiency in widely-used microbiological methods. The Aylward lab is a vibrant and dynamic work environment that welcomes
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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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optimize LIFU as a new human brain mapping tool and for translation to clinical therapies in addiction, mental health and pain. Knowledge in basic computer skills, record keeping and experience with human
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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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, materials, virology, computational biology, science communication, community engagement, and ethics. Candidates should demonstrate all relevant qualifications (see required and preferred qualifications below
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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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include in vitro neural differentiation, gene expression manipulation, metabolic assays, and mouse breeding and behavior. Knowledge in basic computer skills, record keeping and experience with data