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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
, or other novel/emerging pollutants - Developing / implementing advance machine learning algorithms for environmental datasets - Attention to detail and careful documentation of work products such as How
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the results and improving the algorithms. It will also involve extensive literature reviews. Applicants must have an undergraduate degree in computer science, have significant experience with deep learning with
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scholars to pursue their finest work. We are part of the Physical Sciences Division which includes departments such as math, statistics, and computer science, as well as several interdisciplinary research
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, bioinformatics pipeline development, and computational analysis of large-scale biobank datasets to study cardiovascular disease genetics. Primary responsibilities include analyzing common and rare genetic
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-state WWAMI (Washington, Wyoming, Alaska, Montana and Idaho) region. The department supports a residency program, four fellowship programs, including Gynecologic Oncology, and is a major teaching site for
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research activities, assists in preparing human subjects protocols, manages and analyzes data across multiple projects. Contributes to building traditional statistical models and machine learning algorithms
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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
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, genetic information, veteran status, marital status, and/or political affiliation. See: http://www.unl.edu/equity/notice-nondiscrimination Minimum Required Qualifications: Master's degree in Artificial
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-modal”) neural + behavioral disease-state models. The purpose of the research project(s) this position supports: The purpose of the research supported by this position is to develop a computational
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Analysis Machine Learning Genetics Molecular Biology References: Developmental mitochondrial complex I activity determines lifespan. Stefanatos R, Robertson F, Castejon-Vega B, Yu Y, Uribe AH, Myers K