382 computer-"https:"-"https:"-"https:"-"https:"-"I.E"-"UCL" positions at Harvard University
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Fellowship program offers comprehensive research, training and professional development opportunities for scholars advancing their careers in history. Fellows pursue their research with support from
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(FAS) is the historic heart of Harvard University. It is the home of Harvard’s undergraduate program (Harvard College, founded in 1636) as well as all of Harvard’s Ph.D. programs (the Harvard Kenneth C
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, manage TPL’s subscriptions, etc. Work with TPL’s Faculty Executive Assistant and Faculty Program manager to identify and improve communications processes as needed including systems to track social media
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(FAS) is the historic heart of Harvard University. It is the home of Harvard’s undergraduate program (Harvard College, founded in 1636) as well as all of Harvard’s Ph.D. programs (the Harvard Kenneth C
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degree preferably in finance or accounting. Exceptional customer service skills required. Must be able to effectively communicate (verbal and written). Computer proficiency in Excel and Word with a strong
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skills. Solid computer skills such as proficiency with Microsoft Office; intermediate to advanced Excel skills required. Demonstrated knowledge of financial principles, budget management, and financial
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Center for Education Policy Research (CEPR) Program Coordinator will provide administrative support to the CEPR Executive Director and core team. They will play an important role in the central functions
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(FAS) is the historic heart of Harvard University. It is the home of Harvard’s undergraduate program (Harvard College, founded in 1636) as well as all of Harvard’s Ph.D. programs (the Harvard Kenneth C
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flexibility, investment and planning under uncertainty, and the macroeconomic and policy implications of energy system transformation. Fellows will engage in rigorous empirical, computational, and theoretical
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research associates to develop and apply theoretical and computational approaches to study complex cell biological systems. The emphasis will be on combining statistical inferences and biophysical modeling