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Engineering at Virginia Tech. The position focuses on conducting experimental and theoretical research in positioning, navigation, and timing (PNT), with particular emphasis on signal processing and receiver
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of packaging designs for high-value product distribution. The ideal candidate will bring strong analytical and experimental skills to address challenges in packaging dynamics, product protection, and sustainable
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of agentic AI systems for accelerating computational catalysis and experimental design. The successful candidate will contribute to building AI-native frameworks that combine physics-based modeling, machine
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models, analyzing and interpreting experimental data, preparing manuscripts and grant applications, and mentoring trainees within the laboratory. A major component of this position will involve mouse
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reports, conference presentations, or related scholarly activities. Preferred Qualifications - Experience analyzing, modeling, and interpreting complex experimental datasets, as demonstrated through prior
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alongside guidance from senior research personnel. Key Responsibilities • Experimental Design: Develop and optimize behavioral and physiological paradigms targeting brain networks. • Data Collection: Conduct
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biology, neurophysiology, or molecular biology. • Evidence of independent experimental design, data analysis, and clear presentation of results. • Strong documentation skills and organizational/time
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ddRADseq, whole genome sequencing, targeted sequence capture, and other emerging genomic technologies. The successful candidate will participate in all aspects of the research program, including experimental
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to address clinically relevant questions with clear translational potential. Postdoctoral fellows receive hands on training across experimental design, data analysis, and advanced methodologies, while building
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applications. The ideal candidate will possess strong analytical and experimental skills to address complex challenges related to packaging dynamics, product protection, and sustainable material performance