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of random fields, the project seeks to illuminate complex analytic phenomena that remain out of reach under traditional deterministic frameworks. Reporting Structure The PDRA will be based in the Department
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per year. The position is supported by the National Science Foundation (NSF) and the University of Minnesota and will provide opportunities for collaboration with mathematicians and computer scientists
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emphasis on electron microscopy (EM) data. Communication: Excellent analytical, oral, and written communication skills. Application Instructions To apply for this position, please submit the following items
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of two experts in computational microscopy and machine learning systems, blending expertise in advanced bioimage informatics and parallel computing: Dr. Min Xu – Affiliated Associate Professor of Computer
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skills and analytical development to support data collection, analysis, and interpretation. • Ability to communicate information clearly and effectively to diverse audiences through appropriate written
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Feynman conjecture (1993) for quintic Calabi–Yau manifolds, the Yamaguchi–Yau finite generation conjecture and the holomorphic anomaly equation conjecture (2004) on the analyticity of curve-counting
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pedagogical and didatic research methods and theories Expertise in quantitative methods and learning analytics for processing and analysing data What you will do Intitiate, plan and carry out practice-based
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learning, particularly reinforcement learning. Demonstrated experience in mathematical reasoning and problem-solving. A solid publication record in reputable scientific journals. Excellent analytical
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evaluation of learning with digital teaching materials Expertise in quantitative methods and learning analytics for processing and analysing data generated by users of the learning resource worldwide. What you