242 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"NOVA.id" positions at Harvard University in United States
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and review of data collection forms and stratification/randomization of studies; statistical programming; data analysis and monitoring; and report writing under the mentorship and supervision of senior
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, cover letter, unofficial copy of PhD transcript, and email contact information for 3 professional references. Contact Information Hiring Manager cbar.recruiting@sdac.harvard.edu Contact Email
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ability to work both independently and collaboratively. Special Instructions Contact Information Melissa Mendez Contact Email mmendez@seas.harvard.edu Salary Range $67,600 – $91,826 Pay offered
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. Master’s degree preferred. Additional Information Appointment End Date: This is a fully benefits eligible term appointment through August 31, 2026, with potential for renewal subject to funding and
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, math, statistics, and/or computer science Experience with programming, data science, and geospatial analysis (especially R, Stata, Julia, MATLAB, or Python) An enthusiasm for empirical research and an
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duties are carried out under the direction of a CBAR senior statistician: Conduct ongoing, periodic and final analyses of data, using specialized statistical techniques and statistical programming
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Information Nicole Grenier BHI Division Administrator 617-496-8956 Contact Email nicole.grenier@cfa.harvard.edu Salary Range $17,000-$19,000 total for three month period. Minimum Number of References Required 3
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). Certificates and Licenses: Valid driver's license needed. CPR and First Aid required. Additional Information Appointment End Date: 06/30/2026 Standard Hours/Schedule: 32.25 hours per week Compensation Range/Rate
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modeling is a plus. Special Instructions Contact Information Professor Daniel J. Jacob Contact Email djacob@fas.harvard.edu Salary Range $67,600 – $91,826 Pay offered to the selected candidate is dependent
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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