22 data-analytics-phd-"https:" Postdoctoral positions at Virginia Tech in United States
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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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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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, with opportunities to publish, contribute to proposals, and gain experience in laboratory and project management. For more information, please visit: https://nmfc.me.vt.edu/. Required Qualifications
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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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Department at #2 nationally in the Electrical and Electronic Engineering category. Required Qualifications • PhD degree in Electrical Engineering, Computer Engineering, or other related disciplines. PhD must
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the Shin Lab: • https://news.vt.edu/articles/2025/07/research_fralinbiomed_shinR01_mmdd.html • https://news.vt.edu/articles/2023/11/research_fbri_shinstress_1123.html Responsibilities: • Lead an independent
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methods, knowledge-graph and ontology-based scientific data infrastructures, and agentic workflows for autonomous hypothesis generation, mechanistic exploration, and design of catalytic systems. Candidates
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modeling. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining. • Experience with analysis of time series data. • Solid
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interests are interdisciplinary modeling (ideally using economic production theory, more specifically Data Envelopment Analysis, system dynamics modeling/agent-based modeling, and/or Artificial Intelligence
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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