823 data-"https:" "https:" "https:" "https:" "University of Cambridge" positions at Harvard University
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with team members to analyze and resolve data and pay discrepancies. Proactively monitors and resolves issues with employee pay errors including Time & Labor and Absence Management as well as data
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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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! Harvard FCU: https://harvardfcu.org/ Job Description Responsible for a comprehensive array of Member Services Representative (MSR) duties: Processes; transactions: deposits, withdrawals, loan payments, etc
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desired. Special Instructions Required materials, to be submitted through the ARIeS portal (https://academicpositions.harvard.edu/hr/postings/15712 ): 1. Cover letter 2. Curriculum Vitae 3. Writing sample
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at https://academicpositions.harvard.edu/postings/15821. Applications must be submitted no later than March 2, 2026. Please note that references will only be invited to upload letters of recommendation after
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. Additional Qualifications We seek candidates who have strong expertise in design in the context of a computational engineering or applied science field such as computer science, applied mathematics, data
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here: https://itacademy.harvard.edu/ . Job Description This position will be responsible for supporting a broad range of systems and applications providing support both on-campus and remotely with a
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projects through to completion. Additional Information Appointment End Date: December 2026. This is a part-time term appointment starting July 2026 through December 2026 . With potential for re-appointment
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and/or federal training grants a plus. Additional Information Standard Hours/Schedule: 35 hours per week Visa Sponsorship: Harvard University is unable to provide visa sponsorship for this position Pre
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scientists—on projects that bridge methods, policy, and practice. Position Description: This role will involve intensive analysis of claims data and related large administrative datasets to support policy