69 machine-learning-"https:" "https:" "https:" "https:" "https:" positions at Harvard University
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/guidelines . Minimum Number of References Required Maximum Number of References Allowed Keywords statistics, biostatistics, computer science, economics, health care policy, causal inference, machine learning
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diverse, inclusive community dedicated to alleviating suffering and improving health and well-being for all through excellence in teaching and learning, discovery and scholarship, and service and leadership
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, or Python); Creating and managing very large datasets; Managing and mentoring research assistants (RAs); Machine learning skills; Writing papers for management and economics journals; Interest in reskilling
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well as Electronics Shop, Machine Shop, and other core facilities and serve as a consultant/subject matter expert. Provide financial management and input for long-range strategic planning, coordinating with the HQI
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on CDC-recommended vaccines. This position will be based in Cambridge, MA. Work is performed in an office environment with extensive computer and meeting use. During the Summer Program months (June-August
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collaborative, impact-focused problem solver who wants to be part of a dynamic team. Information about the Shih Lab: Learn more about the innovative work led by Dr. William Shih here: https
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dynamic team. Information about the Shih Lab: Learn more about the innovative work led by Dr. William Shih here: https://www.shih.hms.harvard.edu/ . What you’ll do: Design nucleic-acid nanostructures and
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demonstrates relevant skills, such as 3-dimensional and spatial design capability and a creative, problem-solving approach. Proficient with computer-aided drafting and 3D modeling software. (The Harvard Art
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, or Stata); · Creating and managing very large datasets; · Machine learning skills. Basic Qualifications A Ph.D. in any business discipline, organizational behavior, economics, statistics, environmental
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manufacturing and maturation of cells and engineered tissues at low cost, and simple biofabrication technologies to build clinical-scale constructs. Learn more about the innovative work led by Dr. Chris Chen here