28 machine-learning "https:" "https:" "CMU Portugal Program FCT" Postdoctoral positions at Virginia Tech in United States
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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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systems for accelerating computational catalysis and experimental design. The successful candidate will contribute to building AI-native frameworks that combine first-principles modeling, machine-learning
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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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business and entrepreneurship, or applied econometrics. • Strong quantitative skills and experience with cutting-edge techniques in data science, econometrics and machine learning, especially in the areas
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& Machine Learning not excluding other modeling frameworks) of safety critical socio-technical infrastructure systems. The candidate will be primarily responsible for writing and submitting refereed journal
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in areas related to quantum information theory, quantum error correction, and machine learning. The position will start in fall 2026 and will be for two years, with a possible 1-year extension pending
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research statement, and a teaching statement as part of the online application no later than June 30, 2025. Additional information about position requirements and responsibilities can be found at http
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, if desired, to successful candidates. More information on Prof. Liselle Joseph and the PHASE research group can be found at the following link: https://www.aoe.vt.edu/people/faculty/liselle-joseph.html
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of the developed estimates; 4) Developing and maintaining models for calculating use-value assessment estimates; 5) Maintaining content on the Virginia's Use-Value Assessment Program's website (http
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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