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with implementation of: existing algorithms and computer software for analyzing omics-based data sets [high-throughput, massively parallel genomic/proteomic/clinical.]; data management and analysis
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computational approaches. We seek to create a positive, high-energy environment with open and honest communication to empower individuals to discover and refine their purpose and grow into the best versions
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interactions, nuclear structure and reactions, electroweak structure, and lepton-nucleus scattering. The candidate will contribute to advancing statistical and computational algorithms to extend the capabilities
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review. You will possess master level quality, accuracy, speed and knowledge for your assigned specialist area and execute reflex testing algorithms. Work schedule: 100% FTE, Fixed Duration Appointment
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statistical programs using STATA, SAS, and/or R and parallel computing • Learn about and implement novel/unfamiliar statistical methods, depending on the candidate’s skills and project needs • Perform
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onto local storage for substantial cost savings for the lab. After this initial project, with mentoring from the Principal Investigator, the computational scientist will oversee and develop algorithms
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associated clinical outcomes. The fellow will be responsible for identifying computational approaches for data selection, processing, and predictions/inference. The expected outcome of the project is to
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design, data analysis, and documentation of experiment results. Job Description Primary Duties & Responsibilities: Develops algorithms and computer software for omics-based data sets [high-throughput
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studies with implementation of: existing algorithms and computer software for analyzing omics-based data sets [high-throughput, massively parallel genomic/proteomic/clinical.]; data management and analysis
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onto local storage for substantial cost savings for the lab. After this initial project, with mentoring from the Principal Investigator, the computational scientist will oversee and develop algorithms