69 phd-in-integrated-circuit-design Postdoctoral positions at University of Minnesota
Sort by
Refine Your Search
-
designs, animal care and handling, travel for research purposes, collecting samples, conducting experiments, preparing interpretation and summaries of results, participating in conferences, manuscript
-
protein function. Maintenance of membrane bilayer integrity and tight control over material transfer across cellular and organellar membranes is central to proper physiological functioning. Dysfunction
-
experimental and computational methods for integrated multi-omics studies. About the Role · Lead independent research projects investigating somatic mosaicism in various tissue types of human or mouse models
-
at the intersection of systems neuroscience and computational modeling. Our lab is broadly interested in Bayesian inference, perception, multisensory integration, spatial navigation, sensorimotor loops, embodied
-
. Expected distribution of duties includes: ● Laboratory benchwork: 75% ● Data analysis, writing, and presentations: 25% Qualifications Required Qualifications: ● A PhD degree in Neuroscience or a related
-
%). • Contribute to data and lab management (5%) Qualifications Required Qualifications: • PhD, DO, MD or similar degree in health sciences or related field • 3+ years experience in biological sciences laboratory
-
to lead a project related to the transport of bacteria in porous media and multiphase flow. A PhD degree in engineering or earth science is needed. 75% - Conduct laboratory experiments related
-
Regular Job Code 9546 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job About the Job: You will be responsible for designing and conducting NIH-funded research
-
Biological Sciences, Coll Of (15) YesNo Boynton Health Service (8) YesNo Cont And Prof Studies, Coll Of (10) YesNo Dentistry, School Of (23) YesNo Design, College Of (4) YesNo Education & Human Devel, Coll (41
-
in the University of Minnesota. The research will focus on applying, developing and implementing novel statistical methods for causal inference, integrative data analysis or/and machine/deep learning