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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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: 100% Laboratory research • Perform experiments at the bench level to support investigative work (DNA/RNA isolation and analysis, protein isolation and SDS-PAGE analysis, standard molecular biology
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new therapeutics and will be in charge for neuromodulation and neuroimaging hardware and software arrangements, collecting and analysis of data, and publishing the new discoveries. Note: Position tasks
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field deployment 30% modelling of whole-farm greenhouse gas fluxes 20% analysis of trace gas flux data and model outputs 30% manuscript writing & publication Qualifications Required Qualifications PhD in
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related to engineering specialized metabolite biosynthetic pathways Essential and Other Functions: (40%) molecular biology and microbiology (50%) Data analysis (10%) Prepare manuscripts and communications
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of hypothesis-driven research projects. 15% – Analysis & Review • Analysis and review of generated data and reviewing previously reported scientific literature. 15% – Scientific writing and presentation Work
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training while also performing services for the University of Minnesota, for which they are compensated. This position will involve analysis of variation in soybean and pea genomes, including natural
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, immunofluorescence, PCR, qPCR, cell-based assays, fluorescence calcium imaging. • Perform data acquisition and analysis, grant and manuscript preparation, and presentation of findings at weekly lab meetings
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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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, working groups Qualifications Required Qualifications: ● PhD in water resources, hydrology, aquatic ecology, limnology, wetland ecology or a related field ● Experience with synthesis and analysis of large