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. Responsibilities: • Design and conduct experimental research on paper-based materials for food packaging applications. • Develop predictive models for packaging performance using machine learning and physicochemical
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detailed research and progress reports. • Teaching: Pursuing limited teaching opportunities as appropriate. A formalized mentoring plan will be co-developed with Dr. Marston at the start of the position
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research and progress reports. • Teaching: Pursuing limited teaching opportunities as appropriate. A formalized mentoring plan will be co-developed with Dr. Marston at the start of the position to align
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the possibility of extension to a third year. The position involves research in collaboration with one or more members of the tenure-line Virginia Tech Math faculty and teaching one course per semester. The primary
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systems. • Develop and implement predictive models for packaging performance using machine learning approaches and physics-based simulations. • Investigate logistics optimization strategies for packaging
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to liquid chromatography-tandem mass spectrometry (LC-MS/MS). 3. Develop and validate QA/QC criteria for analytical methods and experiments, and prepare documentation and SOPs as needed. 4. Participate in
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manufacture. We continue to push innovation for CLT and wood materials through research, education and outreach. We seek a highly motivated and collaborative researcher with expertise in wood science
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. The position involves research in modeling and simulation of within-host virus dynamics, theoretical immunology and multiscale immune-epidemiological models of infectious diseases and teaching two classes per
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hub dedicated to advancing, implementing, and disseminating state-of-the-art applied economic problem-solving informed by data analytics solutions. The successful candidate will develop a strong applied
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Forest Sector Industry: A Mixed-Methods Approach.” This interdisciplinary research initiative integrates stakeholder engagement, market analysis, and policy evaluation to develop a strategic