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water-related datasets ● Proven track record of leading preparation of scientific publications ● Ability and interest in working collaboratively and effectively as part of a research team that includes
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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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adapt to ever changing needs Preferred Qualifications: ● Research experience in natural language processing on biomedical and/or clinical texts, computer vision on medical images, causal inference
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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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organizational, quantitative analysis and writing skills are necessary. Candidates with a strong background in molecular virology, next-generation sequencing, Bayesian analysis, phylogenetic analysis, statistical
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project that aims to develop new tools to gauge retinal health and disease using next-generation CRISPR-based tools. The ideal candidate who fills this position will have a consistent track record of
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Required Qualifications: Ph.D. in Plant Pathology, Genetics, Molecular Biology, Plant Biology or other related fields; Prior experience with plant pathogens and/or plant tissue culture; A proven track record
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visits into TASCS (Time and Study Collection System). Maintain updated services, visits, subject tracking, and billing grids. Field patient calls related to scheduling and billing. Coordinate with
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to research sites in Minnesota with intermittent overnight stays at field stations or similar accommodations Preferred Qualifications: - Promising record of research productivity - Track record of publication
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regulatory network inference, cell lineage reconstruction, multi-dimensional data integration and etc. * Discuss with the laboratory members in bioinformatics analysis as needed. * Maintaining an active role