33 computer-science-data-wahrn-hous Postdoctoral positions at Virginia Tech in United-States
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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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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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Qualifications -Postdoctoral associate applicants must have a background in quantum information and hold a Ph.D. in Theoretical Physics, Theoretical Quantum Chemistry, or a closely related field. PhD must be
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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
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microenvironment to drive malignant progression. Our research lies at the intersection of glial biology and brain cancer, with a particular emphasis on malignant glioma, the most aggressive form of primary brain
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to work in a dynamic, multi-disciplinary research environment. We value innovative and rigorous science in a friendly and fun environment. Postdocs will have access to all Virginia Tech and Children’s
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on their research and innovation campus. Required Qualifications - PhD and/or MD in Computational Biology, Bioinformatics, Genomics, Biology, Data Science, Computer science or other related fields. PhD must be
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, particularly turbulence in the boundary layer; developing new high-speed measurement techniques, particularly using optical diagnostics methods; augmenting experimental data with Computational Fluid Dynamics
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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
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critical role in advancing computational materials science by developing and applying first-principles and machine learning methods, with a focus on interatomic potential development and large-scale