22 machine-learning "https:" "https:" "https:" "https:" "https:" positions at University of Virginia
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to study chromatin and gene regulation in mammalian cells and human disease systems. Current ongoing projects include: statistical modeling and advanced machine learning/AI method development for predicting
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Energy Spectroscopic Instrument (DESI), Simons Observatory (SO), the Legacy Survey of Space and Time (LSST). We are also interested in candidates who will apply Artificial Intelligence/Machine Learning
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data issues. Utilizing machine learning techniques as appropriate for data analysis. Developing computing programs and software to support research initiatives. Applying new methodologies to real-world
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The Department of Electrical and Computer Engineering at the School of Engineering and Applied Science at the University of Virginia is seeking qualified candidates for a Research Scientist position
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, and MR spectroscopic imaging using machine learning; candidates with experience in these areas are encouraged to apply. PREFERRED QUALIFICATIONS: APPLICATION PROCEDURE: Apply online at https
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statistical methods, machine learning approaches, and AI-driven computational tools. The Biostatistician will work under the supervision of Dr. Ziqiao Wang and there will be opportunities to collaborate with
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ability to learn new information quickly. EMRO collaborates with study investigators inside and outside of the Emergency Department. Therefore, this role offers the ability to work at a high level with both
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. This position will focus on developing and applying novel statistical methods, machine learning approaches, and AI-driven computational tools, with a strong focus on statistical genetics and genomics
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machine learning. The research associate is expected to conduct research on human-fires interactions in built environment. QUALIFICATION REQUIREMENTS: A PhD in atmospheric science, geography, environmental
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Dr. Teague Henry at the University of Virginia invites applications for a post-doctoral research associate with expertise in intensive longitudinal data, machine learning, and digital intervention