28 phd-in-computational-mechanics-"KHALIFA-UNIVERSITY" Postdoctoral positions at Virginia Tech
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and data-driven modeling approaches to understand mechanisms that drive stress contagion. In addition to teaching two lower-division mathematics classes per year, the postdoc will also be responsible
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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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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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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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, 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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aggression, with consideration of intervening social-cognitive interpersonal mechanisms. We have additional lines of research considering sex and gender differences in how stress and trauma impact broader
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existing expertise while providing opportunities to gain new skills in a collaborative and productive research environment. Required Qualifications - Ph.D. in Biology, Neuroscience, or a related field. PhD
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Qualifications - PhD in neuroscience, computer science, or related field. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining
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development of 5G testbed being developed at Virginia Tech and be involved in UAV experimentation with 5G. Required Qualifications - PhD in Computer Engineering or Computer Science or a related field. PhD must
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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