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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
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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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journals and/or top tier IEEE/ACM conferences. • Strong theoretical background in mathematics and analytical thinking, demonstrated by a track record of fundamental research in signal processing
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Job Description The Nuclear Materials and Fuel Cycle Center (NMFC) at Virginia Tech seeks a highly motivated Postdoctoral Associate to lead and support projects on corrosion and materials
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implement MR-based simulation platforms for training and process enhancement in remote construction. Apply machine learning techniques for optimizing construction assembly processes, predictive analytics, and
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of the appointment with a minimum of one year of eligibility remaining; Experience in collecting, managing, processing, and analyzing large datasets; Outstanding database management and analytics skills, including
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applications to biological questions. • Solid background in coding. • Demonstrated ability to work effectively with a diverse team from multiple disciplines. • Demonstrated ability or potential to lead graduate
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factors engineering, and others). - Demonstrated ability to mentor and lead graduate student research. - Previous experience in publishing in high-impact peer-reviewed journals or conferences. - Strong
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by posting number 534603. For full consideration submit a cover letter, a CV, a research statement, and a teaching statement as part of the online application no later than November 20, 2025. Each
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remaining. • Self-motivated and able to work independently and collaboratively • Strong communication skills • Proficiency in R, Python, or MATLAB • Familiarity with spatiotemporal analytical approaches and