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lead several parallel implementation efforts for Merit's business systems, organization risk preparedness, and corporate software development needs. Manage medium to large-scale projects determined by
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. Clinical faculty have 9-month academic year appointments and are eligible for summer financial support for case coverage, special projects, and writing. They have governance rights that closely parallel
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, this candidate will aid in the creation of computationally efficient tools (in Python, R, and bash) to organize, manage, and analyze genomic and genome-wide association study datasets using massively parallel
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Consortium (AC) at the University of Toronto (U of T) is leading a transformative shift in scientific discovery that will accelerate technology development and commercialization. The AC is a global community
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. Clinical faculty have 9-month academic year appointments and are eligible for summer financial support for case coverage, special projects, and writing. They have governance rights that closely parallel
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) to organize, manage, and analyze genomic and genome-wide association study datasets using massively parallel computing infrastructure in the Minnesota Supercomputing Institute (MSI) and Google Cloud (50
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computing clusters, parallel processing, and data pipelining. Strong analytical and statistical background, with the capability to interpret complex biomedical data accurately. Direct experience handling and
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modeling. Extensive experience working with high-performance computing clusters, parallel processing, and data pipelining. Strong analytical and statistical background, with the capability to interpret
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& Responsibilities: Designs, develops, and implements: Algorithms and computer software for omics-based data sets [high-throughput, massively parallel genomic/proteomic/clinical.] Data management and analysis
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Description Primary Duties & Responsibilities: Implements: Algorithms and computer software for analyzing omics-based data sets [high-throughput, massively parallel genomic/proteomic/clinical]; Data management