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Job Description JOB DESCRIPTION The Department of Orthopaedic Surgery and Sports Medicine is seeking a 100% FTE Research Study Assistant for studies examining surgical outcomes of shoulder surgery. The position requires availability from 8:30 am – 4:30 pm Monday through Friday. The Research...
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. The successful candidate will be a member of a highly interdisciplinary team including oncologists, biologists, engineers, and imaging scientists. The candidate will develop computational models of human disease
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, and natural beauty. The Department of Biomedical Informatics and Medical Education provides training, research, and service in education and informatics across the breadth of health sciences and health
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Experience: No additional work experience beyond what is stated in the Required Qualifications section. Skills: Computer Literacy, Confidential Data Handling, Customer Service, Detail-Oriented, Flexibility
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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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geometry, developing a cooled atomic tritium source, and leading design work for Project 8’s future neutrino mass measurement experiments. The postdoctoral positions will be based in Seattle within
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methodologies in brain diseases. The candidate will work on developing advanced new algorithms, testing and validation, and applications in these data modalities. The candidate will have the opportunity to work
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utility for ongoing analysis. Understand key data sources and variations in these across and within countries. Apply computational and statistical tools and algorithms for the preprocessing, analysis, and
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and within countries. Apply computational and statistical tools and algorithms for the preprocessing, analysis, and visualization of source data. Review, assess and improve results, methods and
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about exploring and applying new statistical, computational, or machine learning techniques to astronomical data sets, and extending current methodology to be applicable in the era of big data. Looking