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and/or development of computational and methodological tools for network neuroscience. The candidate is expected to contribute to publications, collaborate with other lab members and external
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to explore opportunities for and develop a medium-term plan for using artificial intelligence tools to support research administration, strategy, and development. The candidate will work with stakeholders
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applying these tools to catalytic reaction engineering and methane conversion chemistry. Required Qualifications - Ph.D. in Chemical Engineering, Chemistry, Materials Science, Physics, or a closely related
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Department of Electrical and Computer Engineering. The Postdoc will particularly participate in the design and development of integrated system-on-chips for wireless sensing, communication, and implantable
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entitled, Evaluation and validation of vegetation, fuel, and fire behavior tools and technology in hardwood-dominated forest ecosystems of Virginia and the eastern United States. The project is being led by
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in vivo neurophysiological recordings and behavioral assays in mice and tree shrews. • Data Analysis: Process large-scale neural datasets, applying computational tools to model behavioral and neural
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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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. 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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tools (e.g., NVivo). - Knowledge of forest sector dynamics, rural development, or bioeconomy transitions. - Experience in publishing peer-reviewed research and developing outreach materials. Pay Band