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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 2 months ago
Postdoctoral Position in Population Genetics and Machine Learning of Autoimmunity The Garber Lab at the University of Massachusetts Chan Medical School (UMass Chan) invites applications for a
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industrial component given the close collaboration with the quantum computing start-up, Quantum Motion, particularly with Dr. Ciriano-Tejel, machine learning group. Key responsibilities Conduct research
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conferences and workshops. The Research Assistant Professor may be asked to teach (or may ask to teach) but that is neither required nor guaranteed. Qualifications Applicants must have a Ph.D. in Economics or
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models to characterize agricultural and ecological systems; Experience in applying advanced Artificial Intelligence/Machine Learning (AI/ML) methods in agriculture (Agro-AI/ML); and Experience in
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and/or testing of samples. May occasionally instruct others in basic laboratory techniques. Working Conditions: Work is performed on-site in Cambridge, MA. May be required to work with a variety of
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command of written and spoken English • Experience with qualitative research methods is an asset • Good knowledge of machine learning /data mining in science • Good programming skills in at least one
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of degree equivalency. Preferred Qualifications: Background in medical imaging, imaging simulation, and machine learning. Programming in Python, MATLAB, C, CUDA. Other Requirements: This position is hybrid
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perform routine logging and/or testing of samples. May occasionally instruct others in basic laboratory techniques. Working Conditions: Work is performed on-site in Cambridge, MA. May be required to work
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associate or bachelor’s degrees through a combination of in-person, online or blended learning. All of our system institutions place strong emphasis on service — helping to build healthier, more educated
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are being developed that provide AI-supported tools to identify suitable sources and optimize utilization decisions throughout the product life cycle. Various machine learning approaches are to be used