667 computer-programmer-"https:"-"https:"-"https:"-"U.S" Postdoctoral positions in United States
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(but are not limited to) Computer Science, statistics, mathematics, automation, informatics, and Engineering. Experience in deep learning, machine learning and medical imaging processing Programming
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 2 hours ago
related field and have a strong background in fMRI data analytic techniques. Computational and quantitative skills are highly desirable. While there will be opportunities for data collection and assessment
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or related areas; demonstrated publications; strong computational skills (e.g., Python, MATLAB); and experience analyzing large datasets and communicating results effectively. PREFERRED : Experience with
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University (University Park). The project is funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development, through program PAR-20-299 (Translational Research in Maternal and
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may include teaching responsibilities. The appointment is generally preparatory for a full time academic or research career. The appointment is not part of a clinical training program, unless research
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning
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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
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to 8 hours/day, lifting <30 lbs, may view computer up to 8 hours/day. Shift Generally Monday – Friday, 8a-5p with some flexibility Job Summary This position is designed to have 70% clinical time, 15
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cytometry and cell sorting. Collect, prepare, and analyze research data; keep a detailed notebook summarizing experiments and recording research data; maintain computer database of research data; tabulate and
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platform for launching an independent academic career focused on AI and the future of scientific practice. Responsibilities Build and maintain computational data pipelines to collect and structure evidence