33 phd-in-mathematical-modelling-population 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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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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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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Genomics. The successful candidate will conduct research in population genomics, comparative genomics, and phylogenomics, with a focus on wildlife species of conservation concern. This role offers
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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
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patient-specific human induced pluripotent stem cells (iPSCs), primary human cells/tissues, along with animal models, to develop a platform for the evaluation of cardiovascular toxicity associated with
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use a combination of patient-specific human induced pluripotent stem cells (iPSCs), primary human cells/tissues, along with animal models, to develop a platform for the evaluation of cardiovascular
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models, human tissue and blood samples. Use biochemical, cellular, molecular, and pharmacological approaches to for mechanistic studies. Use cutting-edge technologies for transcriptomic, proteomic, and