708 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" positions at Harvard University in United States
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, and AI/machine learning would be helpful for the role. Experience with participant recruitment and retention as well as clinical human subject studies is a plus. Special Instructions Application
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astrophysics, exotic core-collapse supernovae, and machine learning methods for time series analysis. A PhD in Physics, Astronomy, or a closely related field is required. The position will entail work on a
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and Harvard’s team and Intercollegiate Ethics Bowl. Travel with Ethics Bowl team to regional and national competitions, as needed. May teach independent study course, as approved through a partnering
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What You’ll Need: PhD in computer science, artificial intelligence, machine learning, computational biology, biomedical engineering, or a closely related quantitative field. Strong foundation in modern
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and learners on our platform. This key technical role requires hands-on expertise across data science, machine learning, and AI solutions. You will manage the lifecycle of artificial intelligence
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Qualifications: HS Diploma or equivalent, required 3-5 years administrative experience directly supporting a high-level manager required. Strong computer skills required, including proficiency with Microsoft
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network engineering and angiogenesis 3). Applications of machine learning in cell and tissue engineering Candidates should have demonstrated publication records in cardiac and vascular engineering or
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travel to New York to support Shop Builds and/or other show-related preparations for up to 2 weeks at a time. Physical Requirements: Ability to sit, type, and work at a computer for extended periods
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acquire on-the-job training, to succeed, and to develop intellectual and practical professional skills. Demonstrated ability to work well in teams is essential. This position will require manual dexterity
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Machine Learning Engineer (MLE) / Data Scientist (DS) to support the end-to-end management, analysis, and visualization of behavioral and clinical data streams. The full-stack MLE/DS will work on studies