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• Skilled in single-cell/population data analysis (e.g., GLMs, decoding) Preferred Qualifications • Background in machine learning or computational modeling (Bayesian methods, neural networks, etc
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on the development of Bayesian statistical/machine learning methods for the data integration analysis of high-throughput imaging and molecular data (i.e., genome, transcriptome, epigenome, and more). The methods would
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applications for a postdoctoral research fellow position. The successful candidate will focus on the discovery and design of immersion cooling fluids using molecular simulation and machine learning methods
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using molecular simulation and machine learning methods. This position offers the opportunity to work at the intersection of computational methods and advanced material discovery in a highly collaborative
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in the ECE - Electrical & Computer Engineering Department. Please include your resume. Job Summary A master's student in the ECE - Electrical & Computer Engineering Department is sought for assistance
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advancements since the opening of the U-M Medical School in 1850. Michigan Medicine is comprised of over 30,000 employees and our vision is to attract, inspire, and develop outstanding people in medicine
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, including the most recent papers. Preference may be given to candidates with knowledge in machine/deep learning, statistical inference, image analysis, survival analysis, causal inference, and high
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Institute (https://cse.umn.edu/aiclimate). The role involves building knowledge-guided machine learning (KGML) models for sustainable agricultural practices, developing AI-ready benchmark datasets, and
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, such as Seurat and Scanpy. Experience with machine learning models, such as transformer and diffusion models. Strong written and oral communication skills. Modes of Work Positions that are eligible
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field. Must be a current Computer and Information Science graduate student at UM-Dearborn Self-motivation and willingness to learn new applications and the ability to work independently Good communication