830 data-"https:" "https:" "https:" "https:" "https:" "https:" "SciLifeLab" "IFM" "IFM" "IFM" positions at Harvard University
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skills, both oral and written, are critical for success. Additional Information Working Conditions: The work associated with this position is performed in an office environment. The role demands
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projects through to completion. Additional Information Appointment End Date: December 2026. This is a part-time (with potential for full-time) term appointment starting July 2026 through December 2026 . With
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possess a current State HVAC license (or equivalent). Must possess a valid driver’s license. Additional Information Location: Harvard John A Paulson School of Engineering & Applied Sciences (SEC); Allston
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possess a current State HVAC license (or equivalent). Must possess a valid driver’s license. Additional Information Location: GSE & Lower Radcliffe Area; Cambridge, MA (USA) Standard Hours/Schedule: 40
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, the development of nutritional strategies, informing policy, the education of researchers and practitioners, and the dissemination of nutrition information to health professionals and the public. The Nutritional
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. Experience in academic, museum, or cultural institution dining environments. Certificates and Licenses: Required DC and food safety management certifications. Additional Information Standard Hours/Schedule: 40
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for program collaboration. Organizes MEI student-focused activities and events. Works with confidential information to assemble and manage guest lists, biographies, and briefing materials for high-level events
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. Cross-Disciplinary Fellowships (CDF) are for applicants with a Ph.D. from outside the life sciences (e.g. in physics, chemistry, mathematics, engineering or computer sciences), who have not worked in
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independently and as part of a team; Superior writing and verbal skills; and A commitment to public-interest lawyering and clinical teaching. Additional Information Appointment End Date: This is a term
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variety of cutting-edge research in time-domain astrophysics, including the development and implementation of machine learning, statistical and data-driven algorithms to study exotic transient phenomena