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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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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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other lab members to design, plan, and implement complex research experiments within the context of a biological research plan (80%) Communicate the findings of scientific studies in publications and at
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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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scholars specializing in dynamical systems modeling of neuronal networks for work on a BRAIN Initiative-funded R01 in collaboration with Gordon Smith at the University of Minnesota and Audrey Sederberg
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effects in pediatric cancer. Collaborate with other researchers to better understand the complex interactions between health determinants and disease outcomes. Extract and analyze large datasets
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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
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., gene knockdown, qPCR, antigen presentation assays) to dissect pathways of cell death sensing • Conduct transcriptomic and pathway analyses (e.g., RNA-seq) to uncover regulatory networks • Generate