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Previous Job Job Title Post-Doctoral Associate - Electrical and Computer Engineering Next Job Apply for Job Job ID 369523 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular
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outside Ability to learn to identify plants Valid driver’s license Ability to travel, including occasional overnight camping Preferred Qualifications: Computer literacy including MS Excel or other
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on applying, developing and implementing novel statistical and computational methods for integrative data analysis, causal inference, and machine/deep learning with GWAS/sequencing data and other types of omic
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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
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research Standard Operating Procedures, the Code of Federal Regulations for clinical trials and Good Clinical Practice guidelines. Computer proficiency and ability to navigate multiple software applications
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. Evidence of being observant and detail-oriented, and the ability to follow written and verbal instructions. Evidence of using a computer and Google workspace, which is the preferred method in sharing data
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host interactions through network analysis, machine learning. - Ability to map microbial genes to biochemical pathway analysis - Excellence in research, communication and collaboration skills, as
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degree -Prior course work in computer analytics and advanced mathematics -Programming experience preferred: SAS, R, STATA and Python -Eligibility for certification using restricted CDC data sets Preferred
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conducting clinical or preclinical proof-of-concept studies Preferred: Experience in physiological signal processing and the application of machine learning to biomedical data Background in computational
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the collective bargaining agreement with the Graduate Labor Union-United Electrical, Radio and Machine Workers of America (GLU-UE). Research Assistant Duties and Responsibilities. This position works closely with