54 Computer-Science Postdoctoral positions at University of Minnesota in United States
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Previous Job Job Title Post-Doctoral Associate - Division of Computational Health Sciences (CHS) Next Job Apply for Job Job ID 366497 Location Twin Cities Job Family Academic Full/Part Time Full
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environments About the Department Neuroscience is the scientific study of the nervous system. It is an interdisciplinary science that collaborates with other fields such as chemistry, computer science
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the next stage of their career. Please direct questions about the position to Cheryl Olman, caolman@umn.edu. Qualifications Required qualifications: PhD in Computer Science, Biomedical Engineering
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to the preparation of manuscripts. Qualifications Required Qualifications: Ph.D. in Bioinformatics or Computational Biology Preferred Qualifications: Experience in preclinical studies, animal handling, molecular
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as Earth and atmospheric sciences, environmental science, hydrology, ecology, computer science, math, statistics, or related fields. Strong programming experience (e.g., Python, Fortran, or C++) and
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Qualifications: •A doctoral degree in a relevant field. "Relevant" is very broad. Scholars from neuroscience, biomedical engineering, psychology, physics, computer science, and many other disciplines have thrived
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Biology, and Development at the University of Minnesota. We are seeking a highly motivated postdoctoral associate to join our team. This role involves developing and applying single-cell systems biology
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Job Code 9546 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job The School of Public Health Division of Biostatistics and Health Data Science (BHDS) is seeking a
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, Environmental, and Geo- Engineering. One would take the lead on a project co-supervised by Profs. Novak and Arnold to evaluate the role of microbial starvation in the degradation of contaminants of emerging
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including engineering of mammalian cell genomes using CRISPR/Cas9 editing, cell cycle synchrony experiments, analysis of chromosome segregation, immunostaining, live cell microscopy, and quantitative image