209 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" positions at BIOMEDICAL SCIENCES RESEARCH CENTRE "ALEXANDER FLEMING"
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button at the top or bottom of the posting on https://jobs.illinois.edu and upload: · A cover letter that details suitability for and interest in the position · Curriculum vitae · Statement
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
position as Teaching Assistant Professor to teach in our undergraduate program, with appointment beginning July 1, 2026 . This is a nine-month position with the responsibility to teach six courses per
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• Skilled in single-cell/population data analysis (e.g., GLMs, decoding) Preferred Qualifications • Background in machine learning or computational modeling (Bayesian methods, neural networks, etc
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Job Description Reporting to the Assistant Director of Upward Bound programs, the Project Advisor is responsible for assisting with the administration, implementation and continuation of the U.S
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mediators using in vivo mouse models. The position has a duration of two years. The project group is part of a vibrant and inclusive research environment (https://www.ous-research.no/kt/) at the Department
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functions. Instructors are needed to teach classes depending upon need and available funding. Applications are accepted on a continual basis (unless otherwise indicated) and will be maintained in pool for two
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and/or related functions. Instructors are needed to teach classes depending upon need and available funding. Applications are accepted on a continual basis (unless otherwise indicated) and will be
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to provide non-tenurable level instruction and/or related functions. Instructors are needed to teach classes depending upon need and available funding. Applications are accepted on a continual basis (unless
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PREFERRED QUALIFICATIONS Experience with innovative teaching methods including problem-based learning (PBL), interactive large and small group presentations, and computer-based interactive teaching programs
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. The project integrates synthetic organic chemistry, kinetic analysis, automation, and machine learning to establish next-generation mechanistic workflows for asymmetric organocatalysis. The project advances