421 phd-position-in-data-modeling-"Prof"-"Prof" positions at Michigan State University
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
Internal Number: 1011222 Working/Functional Title Business Intelligence Supervisor Position Summary As a valued member of the Advancement Services, Solutions team, the Business Intelligence supervisor will
-
socio-economic data in driving the model and using outcomes to understand social dimensions of irrigation and groundwater use, and their role in the Earth system. There will be ample opportunities and
-
socio-economic data in driving the model and using outcomes to understand social dimensions of irrigation and groundwater use, and their role in the Earth system. There will be ample opportunities and
-
/Natural Resources Internal Number: 985226 Position Summary The position provides support for a NASA funded research project. Knowledge and skills in spatial modeling, data/information synthesis
-
are regulated by K17 to regulate immune microenvironment in head and neck cancer models. The applicant must have a PhD in the area of microbiology/immunology/molecular biology or a related field and have a strong
-
neck cancer and what factors are regulated by K17 to regulate immune microenvironment in head and neck cancer models. The applicant must have a PhD in the area of microbiology/immunology/molecular
-
veteran status. Required Degree Doctorate -Physics or related field Minimum Requirements As a PhD in Physics (or related field) is a minimum requirement to be appointed to this position, candidates must
-
applications for a highly motivated Postdoctoral Research Associate in the area of Watershed Modeling and Data Analytics. This position is part of MSU’s Agricultural Climate Resiliency Project(https
-
applications for a highly motivated Postdoctoral Research Associate in the area of Watershed Modeling and Data Analytics. This position is part of MSU’s Agricultural Climate Resiliency Project(https
-
data and develop Artificial Intelligence (AI) prediction models for agricultural production traits. This will involve the integration of AI imaging methods with phenomics to generate predictive tools and