38 modelling-complexity-geocomputation Postdoctoral positions at University of Minnesota
Sort by
Refine Your Search
-
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
-
experiments independently from start to finish, trouble shoots, and optimizes methods. Analyzes, interprets, and presents complex experimental results. Performs statistical analyses. Understands models
-
analysis of data including measures of pupil dilation, microsaccades, and behavioral measures of speech perception. Experience with data collection and statistical modeling of time-series data are essential
-
modeling, physiological signal analysis, and innovative neuromodulation strategies for neurological disorders such as epilepsy, chronic pain, and autonomic dysfunctions. Primary Responsibilities 35
-
, Molecular Biology, or a closely related biomedical field • Experience with retinal immunopathology, photoreceptor biology, or RPE-related degenerative disease models • Demonstrated expertise in retinal
-
study macromolecules and macromolecular complexes involved in membrane transport, homeostasis, and biogenesis, with a particular focus on pinpointing lipid/protein interactions in context of membrane
-
modeling. 80% research - The project focuses on developing theoretical models using optimization and information theory to improve understanding of plant hydraulic regulation at the leaf, plant, and
-
with mouse models of neurodegenerative diseases, demyelinating conditions, and brain tumors • Expertise in flow cytometry, including high-dimensional (spectral) flow cytometry for immune phenotyping
-
and their application in animal models. There will be opportunities to lead a team of students, contribute to grant writing, engage in professional development, and disseminate results at conferences
-
skills in R programming - Working knowledge of Python - Experience with basic analyses to characterize gut microbiomes, including diversity analysis, differential abundance analysis, modeling microbial and