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supervision of Prof. Yingda Cheng on computational methods and modeling for kinetic equations. The research conducted will involve development of numerical methods, development and analysis of reduced order
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candidate will join Dr. Siddharth Saksena’s research group, which focuses on advancing hydrologic modeling, flood forecasting, and hydroinformatics through the integration of artificial intelligence, physics
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models for compressible hypersonic flows; implementing new models and numerical schemes into larger, existing hypersonic CFD codebases; performing verification & validation studies for the new models
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in mouse models. • Carry out molecular and cellular techniques, including molecular cloning, brain sectioning, cardiac perfusion, and immunohistochemistry. • Conduct tissue culture and assist in viral
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machine learning for next-generation wireless networks, (ii) Foundations of semantic communications and age of information, (iii) Stochastic geometry and spatial modeling of large-scale wireless systems
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jurisdictions utilizing land use-value assessment estimates. Duties include, but are not limited to: development of computational methods, maintenance of current models and data sets, identifying and testing
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. - Strong proficiency in machine learning, optimization algorithms, and computational modeling applied to construction systems. - Experience with designing and conducting experimental studies to evaluate
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CRISPRai and optogenetic control systems and developing predictive metabolic models for the oleaginous yeast Yarrowia lipolytica. This position offers a unique opportunity to conduct cutting-edge research
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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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work with colleagues from Virginia Tech and other collaborating universities to run, analyze, and model human evacuation experiments. Data will include motion capture and psychophysiology data to explore