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on the development of Bayesian statistical/machine learning methods for the data integration analysis of high-throughput imaging and molecular data (i.e., genome, transcriptome, epigenome, and more). The methods would
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development across the lifespan, including: the psychological foundations of education, quantitative methods in education, the practice and science of counseling psychology, school psychology, and special
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-cell and omics approaches, our methods allow for in-depth exploration of intracellular signaling networks and physical interaction networks in health and diseases. Using these methods, we aim
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. conducts literature searches for methods and procedures specified by the principal investigator; plans and develops assays to evaluate experimental methods and techniques. (15%)- Manage research results and
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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