12 bayesian-network Postdoctoral positions at University of Minnesota in United States
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methods of data analytics (e.g., statistics, stochastic analysis, Bayesian statistical analysis), physically-based hydrology and water quality models, and the use of machine learning tools for modeling flow
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plasticity metrics derived from functional MRI data. Investigate developmental differences in brain functional networks Support generation and testing of improvements for code bases for the analysis
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, or a related technical field. ● Strong programming skills in Python, Java, etc. ● Expertise in machine learning, neural networks, and deep learning ● Excellent writing and communication skills ● Highly
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host interactions through network analysis, machine learning. - Ability to map microbial genes to biochemical pathway analysis - Excellence in research, communication and collaboration skills, as
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Statistical Research Data Center (FSRDC) network). Diversity and inclusion are core values of MPC. We aspire to create a team that represents the diversity of our city, our region, and our world, and to create
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gap between how artificial and real networks learn. The Department of Neuroscience at the University of Minnesota is home to a strong and collaborative community studying motor learning and motivational
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experiments using murine models to study immune regulation and retinal degeneration • Conduct transcriptomic and pathway analyses (e.g., snRNAs-seq, RNA-seq) to uncover regulatory networks • Use molecular and
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musculoskeletal biology; all of these groups offer regular seminars, journal clubs and social/networking events. Responsibilities: • Planning, execution, analysis, documentation and communication of novel research
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between neuromodulation and fMRI. The postdoc will work on the network level perturbation of neurocircuits using high-definition neuromodulation. This postdoc will lead scientific discovery in developing
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plasticity metrics derived from functional MRI data. Investigate developmental differences in infant brain functional networks Support generation and testing of improvements for code bases for the analysis