60 phd-mathematical-modelling-ecological-modelling Postdoctoral positions at University of Minnesota
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are subject to change as research needs change. It is expected that up to 20% of job duties may change annually. Qualifications Qualifications: PhD degree required in ecology, plant or microbial biology
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the atmosphere and understand transport pathways by combining observations of PFAS in precipitation from the National Atmospheric Deposition Program with atmospheric modeling techniques. This position primarily
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Qualifications PhD in cell biology and biophysics. Training and/or experience in handling of purified proteins, computational analysis and modeling in MATLAB, stem cell differentiation and tissue culture, confocal
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Responsibilities: Conduct basic, translational, and clinical research involving animal models and/or human subjects. Design and implement experiments related to auditory perception and neural coding Develop and
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mainly be responsible for developing the building blocks of a forest planning model (adapting inventory data, assessing current growth and yield projections, defining current forest management strategies
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-channel electrophysiology •Any prior work in mathematical models of decision-making •Prior work with psychiatric patient populations or the biological mechanisms of mental illness About the Department
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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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graduate students Qualifications Required Qualifications: PhD that included bioinformatic and statistical analysis of microbiome, metagenomic, and/or WGS data Experience with basic molecular techniques
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Redshift Survey (GRS) team. The appointment will focus on simulations and analysis that underpin the survey: end-to-end grism simulations and realistic mock catalogs; modeling and optimization
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Dr. Shen Cheng and his internal/external collaborators. The research will primarily focus on implementing and developing innovative pharmacometric modeling approaches for pharmacokinetic