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profiles, to identify treatment response patterns, subtypes, and critical intervention windows that reduce Alzheimer's risk Disease (AD) risk. This position will involve applying machine learning, deep
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Qualifications Experience with Matlab, Phyton, C++ or other programming languages. Experience with remote sensing (multispectral and thermal IR). Experience with LiCOR measurements. Experience with machine
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Associate to join the Artificial Intelligence (AI) & Machine Learning (ML) Lab, under the direction of Dr. Bo Liu. The team is a collaborative partnership between nine Universities across the US led by the
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to work on a project at the intersection of deep learning and computer security/privacy, under the direction of Dr. Michael Wu. The project seeks to investigate security and privacy problems in deep
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imbalances. A fundamental understanding of classical Machine Learning Techniques for longitudinal data analysis. An understanding of probability theory and basic frequentist statistical approaches
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to estimate ET water loss, while analyzing various other existing ET products. Advancing hydrological models (e.g., the National Water Model, land surface models) with machine learning techniques to improve
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, learning analytics, AI in education, and/or machine learning Self-motivated, detail-oriented with excellent organizational, written, and oral communication skills Proficiency in academic writing in English