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of Minnesota, working with Professor Russell Funk. This position focuses on using computational methods to understand how knowledge is produced, shared, and applied across complex systems. About the Project
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Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job The primary responsibility of this postdoc position will be to probe for Beyond the Standard Model physics in the Mu2e
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model development. -Proficiency in molecular and cellular biology techniques (e.g., DNA/RNA extraction, flow cytometry, histology, fluorescence imaging). -Proven record of first-author publications in
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the REVEAL project, in which vagus nerve implant patients will be stimulated with various settings, and corresponding responses will be collected across body systems. Multiple types of computational and
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neurophysiology using animal models. Knowledge in hearing science, hearing impairment, perception, and computational modeling of neural systems. Proficiency in programming for data analysis and modeling (e.g
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the atmosphere and understand transport pathways by combining observations of PFAS in precipitation from the National Atmospheric Deposition Program with atmospheric modeling techniques. This position primarily
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Qualifications: Strong background in modeling and analytical skills using OpenSees and Abaqus. Experience in large-scale testing. Previous design experience in North America is considered an asset. Proficiency in
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, protein design, engineering and purification, strain engineering and microscopy (fluorescent, TEM, SEM, AFM) and analytical methods (HPLC, GC, rheology) and/or computational analysis/modelling of biological
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mainly be responsible for developing the building blocks of a forest planning model (adapting inventory data, assessing current growth and yield projections, defining current forest management strategies
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of the observing program; studies to model and mitigate observational systematics; and delivery of high-level products. These efforts are intended to enable robust BAO and RSD measurements from Roman GRS data and to