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the management, analysis, and presentation of laboratory data and clinical data providedby our clinical collaborators who obtain the muscle biopsies. Making use of these data, the successfulcandidate will assist
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Chekouo and his collaborators within and outside the University of Minnesota. The research will focus on the development of Bayesian statistical/machine learning methods for the data integration analysis
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Associate I, Immunobiology Posting Number req26998 Department Immunobiology Department Website Link https://immunobiology.arizona.edu/ Location Tucson Campus Address 1501 N. Campbell Ave., Tucson, AZ 85719
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research Experience with machine learning, deep learning, or multimodal data analysis Experience conducting human-subject research and IRB-compliant studies Experience working with healthcare systems
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dependent educational benefits Life insurance coverage Employee discounts programs For detailed information on benefits and eligibility, please visit: http://uhr.rutgers.edu/benefits/benefits-overview
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dependent educational benefits Life insurance coverage Employee discounts programs For detailed information on benefits and eligibility, please visit: http://uhr.rutgers.edu/benefits/benefits-overview
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will be involved in the preparation of scientific manuscripts and competitive research proposals, contributing to the writing, data analysis and presentation of results. LanguagesENGLISHLevelGood
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(minimum 80% FTE) Reporting to Professor Rachel Upthegrove, you will work specifically on analysis of two completing trials with clinical, biomarker and imaging data: Psychosis Immune Mechanism Stratified
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-based products. The candidate will be involved in data collection, quantitative data analysis, interpretation of findings, preparation of deliverables, writing of academic articles and ongoing development
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cytometry, and microscopy are encouraged to apply. Additionally, previous experience analyzing transcriptomic data is an advantage, as the dry lab (e.g., single cell RNA-sequencing dataset analysis) informs