63 phd-mathematical-modelling-ecological-modelling Postdoctoral positions at University of Minnesota
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Previous Job Job Title School of Mathematics Post-Doctoral Associate (AY25-26) Next Job Apply for Job Job ID 370926 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular
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Previous Job Job Title Dunham-Jackson Postdoctoral Associate - School of Mathematics Next Job Apply for Job Job ID 370276 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular
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across time and contexts. Job Description: You will develop and apply mathematical models and machine learning algorithms to analyze the structure and evolution of knowledge systems across different
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Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Duties: 85% lead soil data analysis, model implementation, and dissemination of research findings 5% development and guide
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for H-1B visa sponsorship. Qualifications *Required qualifications include: -PhD in Biomedical Sciences, Biomedical Engineering, or a closely related field. -Demonstrated expertise in thermal modulation
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of stable isotopes, mass spectrometry, and computational modeling to quantify in vivo metabolic fluxes in genetically-engineered mice. Under the direction of Curtis Hughey, the postdoctoral associate will
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well as field, greenhouse, and laboratory studies focused on applied ecology, Integrated Pest Management (IPM), and Insect Resistance Management (IRM) for lepidopteran and coleopteran pests, and other duties
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metabolism in model systems. ● 15% Publication and presentation of data → The postdoctoral scholar is expected to communicate their research findings through publication in peer-reviewed research journals and
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and well-being or examines socio-ecological determinants of health Excellent written and oral communication skills as demonstrated by publication record and conference presentations Advanced statistical
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machine learning analyses will be performed to determine correlations across stimulation settings and body systems as well as to develop predictive models and biomarkers for physiological and clinical