34 phd-mathematical-modelling-ecological-modelling Postdoctoral positions at The University of Arizona
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, joins, JSON operations. Minimum Qualifications PhD degree in computer science, informatics or related discipline such as applied mathematics. Two (2) years of experience with using the following neural
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murine BMT models, and donor graft manipulation and pharmacological interventions. Candidates should have a PhD or MD and a strong foundation in cellular and/or tumor immunology. Candidates with a
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://phoenixmed.arizona.edu/cts/phd Location Greater Phoenix Area Address Phoenix, AZ USA Position Highlights The Radovick Lab at UArizona Phoenix has an opening for a post-doctoral researcher to study the role
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supported by multiple NIH R01 grants and focuses on molecular immunology and inflammatory mechanisms. Cutting-edge research models (eg. primary cell/organoid cultures, mouse models and human clinical samples
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representation learning, and real-world data modeling to stratify risk and optimize MHT formulations. The candidate must thrive in a multidisciplinary, fast-paced research environment and work independently and
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Qualifications Upon hire, a PhD or equivalent in a relevant field including, but not limited to ecophysiology, evolutionary ecology, behavioral ecology. Proven record of publications. Preferred Qualifications
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viral and microbiome studies. Apply statistical models to analyze genomic, ecological, and disease data, including species diversity analyses. Prepare and submit manuscripts for peer-reviewed journals and
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Number req22961 Department Ecology & Evolutionary Biology Department Website Link Location Main Campus Address Tucson, AZ USA Position Highlights The McNew Lab at the University of Arizona seeks a
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should have a PhD, DVM, MD or MD/PhD and a strong foundation in genomics, genetic intervention techniques and immunology. Candidates with a background in lung research and experience with rodent models
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the Department of Energy (DOE) for the first sponsored The ICDI Emerging Tech Postdoctoral Program. The selected candidate will work on an exciting interdisciplinary project focused on developing predictive models