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Field
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, computer science, machine learning, and education research. Research Themes The research themes identified for the NTO postdoc include, but are not limited to, the following: Developing or evaluating methodologies
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. Develop advanced optimization, control, or machine learning strategies for distribution systems; validate these strategies using hardware-in-the-loop or real-time grid simulators. Develop optimization
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, and socially meaningful scholarship. Required Qualifications: Applicant must have a PhD in psychology, human development, quantitative psychology, or a related area. Strong background/interests in
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artificial intelligence (AI) and machine learning (ML) methodologies and interested in advancing these tools for accelerating the analysis of the big data acquired by electron microscopy. • You work
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• Effective communication skills Preferred Qualifications • Expertise in one of the following areas: Environmental or Performance Physiology, Machine Learning, Motion Analysis, Multiscale Modeling
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a PhD in agricultural and resource economics, economics, or related field by the start of the position. The ideal candidate has a strong quantitative background (econometrics and causal inference
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with both research and teaching responsibilities. Preference will be given to candidates whose expertise aligns and strengthens the research of the Department. The successful candidates must have a PhD
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opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by joining our team and exhibiting your passion and pride in your work as part of our
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experience. Research background in decision making systems, in particular the use of different optimization, machine learning, and decision making modeling techniques for problem solving. Desire to grow
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) in the department and in the Great Plains IDeA-CTR network, and growing institutional strengths in AI, machine learning and clinical informatics. This is a unique opportunity to translate and expand