34 postdoctoral-modelling Postdoctoral positions at University of Minnesota in United States
Sort by
Refine Your Search
-
Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job An NIH-funded postdoctoral position is available for a two-year program in the laboratory of Brendan Dougherty within
-
of Minnesota is seeking two postdoctoral research associates to join a team working on multiple research projects in the field of health data science, artificial intelligence and natural language process
-
is seeking a postdoctoral associate for a funded project on evolutionary responses to climate change and consequences for geographic range dynamics. Our project specifically focuses on improving
-
neural populations and their application in animal models In the Department of Neurosurgery. There will be opportunities to lead a team of students, contribute to grant writing, engage in professional
-
quality models to better understand the effect of soil health management practices on soil-water storage in agricultural fields. A postdoctoral position is available to examine the effect of soil health
-
of Minnesota is seeking a highly motivated Postdoctoral Researcher to join a dynamic team focused on developing intelligent neurotechnologies for translational medicine. The lab specializes in computational
-
Regular/Temporary Regular Job Code 9546 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Postdoc in urban stormwater pond dynamics We are seeking a postdoctoral
-
and then model their space use and behavioral patterns. The post-doctoral researcher will also be responsible for coordinating a team to deploy and monitor behavioral playback cameras, developing a data
-
, Molecular Biology, or a closely related biomedical field • Experience with retinal immunopathology, photoreceptor biology, or RPE-related degenerative disease models • Demonstrated expertise in retinal
-
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