66 phd-mathematical-modelling-ecological-modelling Postdoctoral positions at University of Minnesota
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development; and opportunities for outreach and community engagement. Qualifications Required Qualifications: PhD in limnology/oceanography/microbial ecology or related field Preferred Qualifications
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at the intersection of systems neuroscience and computational modeling. Our lab is broadly interested in Bayesian inference, perception, multisensory integration, spatial navigation, sensorimotor loops, embodied
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agreements on a temporary or permanent basis for any reason at any time. All required qualifications must be documented on application materials. Required Qualifications: • PhD in Retinal Biology, Immunology
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have a PhD in environmental engineering, earth or environmental engineering, or related fields, with a background in ecohydrology. Experience in ecohydrological modeling and remote sensing is desired
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and their application in animal models. There will be opportunities to lead a team of students, contribute to grant writing, engage in professional development, and disseminate results at conferences
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tissue culture, experimental virology, transcriptome analyses, and immunologic assays. Prior experience conducting relevant experiments using in vitro and in vivo models of infection, such as flow
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-activated immunogenicity, scaled-up vector production, and assessment of AAV efficacy in pre-clinical animal models. The goal of our research is to ensure advancement of gene therapy treatment for patients
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required qualifications must be documented on application materials. Required Qualifications: • PhD in Immunology or a closely related biomedical field • Strong scientific knowledge and hands-on experience
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Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job The research will focus on hybrid AI modeling and agroecosystem sustainability, in collaboration with the AI-CLIMATE
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methods of data analytics (e.g., statistics, stochastic analysis, Bayesian statistical analysis), physically-based hydrology and water quality models, and the use of machine learning tools for modeling flow