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• Skilled in single-cell/population data analysis (e.g., GLMs, decoding) Preferred Qualifications • Background in machine learning or computational modeling (Bayesian methods, neural networks, etc
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teams. Familiarity with uncertainty quantification and parameter calibration methods. About the Department The Department of Bioproducts and Biosystems Engineering (bbe.umn.edu) is an internationally
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, qPCR, drug development, experimental design, data analysis and recording primary data and methods used. 5% Research communication Critical analysis of the literature, preparing manuscripts, oral
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electrophysiology or optical stimulating/recording methods. •Experience working with awake, behaving rodents is essential, which could include work using pharmacologic manipulations. •Prior experience in highly multi
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proper laboratory methods and procedures. Qualifications Required Qualifications: - A Doctorate Degree (PhD, which is completed within the last 2 years) in relevant scientific fields (neuroscience
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Colelcotricum coccodes. (10%) Recording field and greenhouse study data and applying statistical methods (e.g., ANOVA, regression) to correlate pathogen load with disease outcomes and field and greenhouse
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combination of mass spectrometry and NMR methods to assess potential risks of these chemicals to coastal ecosystems. These individuals will also interact with, lead, and assist graduate and undergraduate
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in the University of Minnesota. The research will focus on applying, developing and implementing novel statistical methods for causal inference, integrative data analysis or/and machine/deep learning
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procedures to engineer, manipulate, and phenotype yeast cells. They will perform molecular, genetic, and microbiology techniques and will be expected to select and adapt methods to meet specific research needs
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Street SE, TC East Bank Campus Description for Zang’s lab: Dr. Zang’s lab focuses on applying quantitative modeling methods to address critical public health challenges, particularly in health equity, HIV