23 numerical-modelling Postdoctoral research jobs at University of Nebraska Medical Center
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Qualifications: PhD (or analogue) and substantial knowledge of human and/or animal reproductive physiology. Significant experience of working with, and breeding rodent models. Excellent communication skills
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adenocarcinoma (PDA) pathogenesis. The murine models of distinct genetic subtypes of pancreas cancer that we have developed form the basis of our integrated, systematic, and multidisciplinary research program. Our
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comfortable with handling research animals (rodent models) and conducting developmental biology and HIV-1 virology linked experiments in these animal models. . In addition, ability to work as a part of a team
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and working experience in BSL2, BSL3 and ABSL2 and ABSL3 labs preferred. Research interests include animal models as synergetic platform for preclinical development of therapeutics and molecular biology
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include animal models as synergetic platform for preclinical development of therapeutics and molecular biology aspects of the diseases. A self-starter with strong interest in understanding virological
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neuroscience, with demonstrated success as a recent Ph.D. graduate with a track record in (1) statistical modeling, (2) tobacco regulatory science, or (3) neurocognition and brain development. The successful
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experience in animal models of pulmonary hypertension are particularly encouraged to apply. The successful applicant will also have experience in directing and training of graduate students and postdoctoral
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investigates molecular and cellular mechanisms of pancreatic ductal adenocarcinoma (PDA) pathogenesis. The murine models of distinct genetic subtypes of pancreas cancer that we have developed form the basis
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adenocarcinoma (PDA) pathogenesis. The murine models of distinct genetic subtypes of pancreas cancer that we have developed form the basis of our integrated, systematic, and multidisciplinary research program. Our
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cell biology, immunohistochemistry, and animal model studies to support the maintenance of existing research projects in brain and lung cancer and, additionally, will contribute to both the optimization