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. • Proficient communication skills. • Track record of conducting original research and publishing in peer-reviewed scientific journals. Preferred Qualifications • Experience in remote sensing or machine learning
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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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. 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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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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, and contact information for 3 references. Required Qualifications - PhD in Mechanical Engineering, Materials Science and Engineering, Polymer Science and Engineering, Electrical Engineering or a related
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or, preferably, scientific machine learning (SciML). • Conducting research related to the improvement of the hygrothermal properties of cross-laminated timber. Desing and perform testing and analysis crate
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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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year. The individual will also be responsible for writing documents, including grant reports and publications. Required Qualifications • PhD in Mathematics or a related field with a background in
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• Ph.D. in Nuclear Engineering, Mechanical Engineering, Materials Science, or a related field. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one
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for field work, project meetings and conferences. Required Qualifications • Ph.D. in Environmental Engineering, Chemical Engineering, Environmental Chemistry, or a related field. PhD must be awarded