14 computing-"https:"-"https:"-"https:"-"P" Postdoctoral research jobs at Virginia Tech
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motivated and collaborative researcher with expertise in engineering, materials science, or related computational fields to contribute to our growing research program in sustainable food packaging. Current
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to align these opportunities with your long-term career goals. Required Qualifications • Ph.D. in Civil Engineering, Hydrology, Computer Science, Earth System Science, or related fields. PhD must be awarded
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systems for accelerating computational catalysis and experimental design. The successful candidate will contribute to building AI-native frameworks that combine first-principles modeling, machine-learning
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Job Description Applications are invited for a National Science Foundation funded (LEAP HI Program #2051685), Postdoctoral Associate position with the System Performance Laboratory (SPL
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research program that works both within and at the boundaries of data science/econometric methods and the social sciences to discover, create, and disseminate new knowledge. The successful candidate will
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and collaborative researcher with expertise in engineering, materials science, or related computational fields to contribute to our research program focused on transport packaging optimization and
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Job Description We invite applications for a postdoctoral associate position in theoretical quantum information science in the Physics Department of Virginia Tech. The successful candidate will work
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, fluorescence in situ hybridization, and bioinformatics. Preferred Qualifications Molecular biology and genetics laboratory experience; web computer skills; ability to learn new techniques and procedures
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with governmental and industry partners. • Familiarity with environmental policy and regulatory frameworks. • Experience in data science, computational chemistry, and/or contaminant transport modeling
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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