119 machine-learning "https:" "https:" "https:" "https:" "https:" "U.S" Postdoctoral positions
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Missouri University of Science and Technology | Rolla, Missouri | United States | about 2 months ago
genome-based influenza and/or SARS-CoV-2 risk assessment algorithms, designing broadly protective influenza and SARS-CoV-2 vaccines using Machine Learning and Artificial Intelligence, modeling the impacts
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related field. Computer Skills Basic computing skills Supervisory Responsibilities No Required operation of university owned vehicles No Does this position require direct animal or patient contact
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undergraduate students. Ability to manage priorities and timelines. Applicants must be U.S. citizens or permanent residents at the time of application. Desired Qualifications: Expertise in the design and testing
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industrial engineering, systems engineering, computer science, electrical engineering, or a related field. · Strong background in machine learning or data analytics and hands-on experience handling big
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focus in machine learning. The postdoctoral scholar will work on topics of mutual interest such as, but not limited to, automatic machine learning model selection and automatically explaining machine
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). • Familiarity with cloud computing and machine learning techniques. Instructions Applications for this position should include a: (1) Curriculum Vitae with the names and contact information of 3 references (2
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students a transformative, globally connected learning experience. Consistently ranked among the nation’s top universities by U.S. News & World Report, Loyola is a STARS Gold-rated institution that is ranked
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. Eisenberg about also applying for the Biological Mechanisms of Healthy Aging Training Program (https://live-uwhalo.pantheonsite.io/uwhalo/bmha/post-doctoral-openings/ ). The position is 100% FTE for 12 months
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sciences.Tackling key problems in biology will require scientists trained in areas such as chemistry, physics, applied mathematics, computer science, and engineering. Proposals that include deep or machine learning