67 data-"https:" "https:" "https:" "https:" "https:" "https:" "Dr" "UCL" "UCL" "UCL" Postdoctoral positions at University of Minnesota
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/qualifications/experience Time Appointment: 100% Appointment Position Type: Faculty and P&A Staff Please visit the Office of Human Resources website for more information regarding benefit eligibility
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Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Supervisor of Position: Dr. Devanshi Khokhani Anticipated Initial Appointment Period: 1 Year Salary Range: $62,232 – $65,000
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for Postdoctoral Candidates website for more information regarding benefit eligibility. Competitive wages, paid holidays, and generous time off Continuous learning opportunities through professional training
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for Magnetic Resonance Research , and the Minnesota Supercomputing Institute . More information about the department is available at https://cse.umn.edu/aem . Pay and Benefits Pay Range: $61,108 - $62,232
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, (ii) environmental modeling and/or advanced data analysis and statistical evaluation techniques, and (iii) treatment of water and soils containing organic contaminants using adsorption or other
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% Detailed documentation of procedures and experimental data is required. This involves analyses of data, writing summary reports on results of work and discussing results with laboratory colleagues and
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and Benefits Pay Range: $62,232/year Please visit the Benefits for Postdoctoral Candidates website for more information regarding benefit eligibility. Competitive wages, paid holidays, and generous
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within the College of Science & Engineering. More information about the department can be found at https://cse.umn.edu/cege Pay and Benefits Fixed Pay Rate: $61,008 annually Please visit the Benefits
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. Experience working with mice, handling primary and continuous cell culture, multicolor FACS staining and analysis is highly desirable. Working knowledge of bioinformatic analysis of omics data is desired but
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. This individual will also assist in developing the infrastructure, tools, and collaborations needed to integrate genomic, transcriptomic, imaging, and clinical data in ways that advance precision veterinary