630 machine-learning "https:" "https:" "https:" "https:" "https:" "The University of Edinburgh" positions at Harvard University
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an inclusive community of dedicated problem-solvers who hold themselves – and one another – to the highest academic and professional standards. To learn more about us, please visit https://seas.harvard.edu
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time management and organizational skills; able to manage multiple priorities in a fast paced, customer focused environment General computer proficiency, including Microsoft Word, Excel, Access, Yardi
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Please see the fellowship page for more information: https://www.huri.harvard.edu/mihaychuk-postdoc-fellowships Additional Qualifications Special Instructions Contact Information Megan K. Duncan Smith
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-2027 dates: https://registrar.fas.harvard.edu/calendars#tenyear). Applicants may consider an early September start date, or a late January start date, for shorter appointments. Review of applications
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assessed for impact. Responsibilities include: In the MDE Program: Co-teach the spring semester of MDE Studio course (STU 1232) annually. Studio is both a space as well as a pedagogical setting which can
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of neural circuits controlling various aspects of natural behavior. See our lab web page (https://www.engertlab.org/research ) for more information about our publications and research interests. Basic
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-motivated with a strong desire to 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
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of and experience with quantitative methods (simulation modeling, optimization, and machine learning) preferred This is an annual term position reviewed each academic year on or before June 30th, with
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scientists, engineers, and/or doctors! The lab is committed to fostering lifelong learners in an environment that is diverse, inclusive and respectful. Learn more about our lab here: https
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, and either flow cytometry or microscopy, or both. The ideal candidate values patience, curiosity, and hypothesis-driven science, and is eager to learn new model systems and/or techniques. High standards