36 computational-modelling Postdoctoral research jobs at University of Minnesota in United States
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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
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, computer vision in the Division of Health Data Science (HDS) at the DOS. The position is an annually renewable professional academic appointment. Duties/Responsibilities: ● Risk predictive model for clinical
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, and publication of major results from the experiment. They will also lead the development of predictive distribution models that incorporate data from the experiment. The project is funded by the USGS C
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flux measurements using biogeochemical modeling. They will be responsible for managing projects related to field instrumentation and ecosystem flux modeling. 20% designing and implementing trace gas flux
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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
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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
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with innovative modeling methods and data analytics methods and spur cross-discipline development between the team in both water resources and computer science. Specifically, the research projects
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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
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% – Conduct computational modeling and/or analyze data from clinical and preclinical studies related to neurological conditions (e.g., epilepsy, chronic pain, autonomic dysfunctions) 30% – Develop grant
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or more of the following: ● Experience with urban watershed modeling or lake systems modeling ● Experience with limnological or aquatic field methods ● Experience with statistical methods for making