94 engineering-computation-"https:"-"https:"-"https:"-"https:"-"https:"-"BioData" positions at Stanford University in United States
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of relevant experience or combination of education and relevant experience. Experience in a quantitative discipline such as economics, finance, statistics or engineering. KNOWLEDGE, SKILLS AND ABILITIES
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, Engineering, Accounting, Finance, Business, or other related field preferred. · Demonstrated track record of successful healthcare improvement leadership and program building. Able to easily facilitate
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gastroenterologists with nationally recognized expertise through their research, teaching, and clinical programs which attracts leading candidates to their fellowship program. We have a mission of healing children
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on “bench to bedside” technology. The primary work will include supporting pilot studies of Pediatric Gastroenterology faculty (from study start up to closure), as well as federally funded and industry
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(Administrative Associate 3) to provide administrative or operational support with limited supervision to 4-6 faculty and their program managers. Faculty will have varying levels of support needs ranging from
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applicant for this position will be passionate about education, have program and project management experiences, and a desire to collaborate with a dynamic group of faculty, staff, and trainees on a mission
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solve work. · Ability to maintain detailed records of experiments and outcomes. · General computer skills and ability to quickly learn and master computer programs, databases, and scientific
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REQUIRED: • Comprehensive understanding of scientific principles • Expert level knowledge and skills in field of science related to research project • General computer skills
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The Childhood Research Obesity Prevention (CROP) research program under the Department of Pediatrics, Division of Gastroenterology, Hepatology, and Nutrition (Pediatric GI) within Stanford
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research. The ideal fellow will be interested in developing and applying novel computational algorithms to novel datasets generated in the setting of non-neoplastic and neoplastic disease. Key