77 phd-position-in-data-modeling-"UCL"-"UCL" Postdoctoral positions at University of Minnesota
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development, and disseminate results at conferences. This position will work Monday-Friday with weekends as needed. Expected distribution of duties includes: ● 75%: Laboratory benchwork ● 25%: Data analysis
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/pharmacodynamic data analysis in the presence of high-dimensional covariates for the improved model-informed decision making. The initial duration of this position is 1 year, but may be extended or a second and/or
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Council, the project will integrate new data collections with existing datasets from recent studies and monitoring programs to understand how pond age, design and management influence trajectories of pond
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skills for this position. Specifically, the PA will use generalized additive mixed-effects models to analyze data from existing and ongoing projects. Fluency with the R programming language is essential
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Arrangement: • The position is expected to work primarily on-site. Your work location will on the 3rd floor, Wallin Biomedical Biosciences. • The Department retains the right to modify flexible work arrangement
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guidelines. Time Appointment: 100% Appointment Position Type: Postdoctoral Associate Please visit the Benefits for Postdoctoral Candidates website for more information regarding benefit eligibility
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/Temporary Regular Job Code 9546 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Duties/Responsibilities: These positions are for Post-Doctoral Associates who will be
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Regular/Temporary Regular Job Code 9546 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Summary of Position: The post-doctoral researcher will work under the
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Immunology 60% Execute experiments 20% Design experiments 20% Analyze data, write grants and papers Qualifications Required Qualifications: PhD in Biology, Chemistry, or related Biomedical Sciences Project
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tissue culture, experimental virology, transcriptome analyses, and immunologic assays. Prior experience conducting relevant experiments using in vitro and in vivo models of infection, such as flow