155 coding-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at Harvard University
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-workers and customers in a professional environment. Must observe and comply with all standard safety codes and practices and perform work in accordance with recognized industry and university standards
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with co-workers and customers in a professional environment. Must observe and comply with all standard safety codes and practices and perform work in accordance with recognized industry and university
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-workers and customers in a professional environment. Must observe and comply with all standard safety codes and practices and perform work in accordance with recognized industry and university standards
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-workers and customers in a professional environment. Must observe and comply with all standard safety codes and practices and perform work in accordance with recognized industry and university standards
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central role in building and scaling our core application platform — the hub within HBS where application developers can share data and code. As custodians of this platform, we will apply best practices and
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Familiarity with modern AI coding tools (e.g., Claude Code) Experience and interest in working in collaborative settings with other team members Additional Information Appointment End Date: Two years from date
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and clinical support for study activities, including participant recruitment, interviews, data collection, coding, and analysis. The Coordinator will work in a highly collaborative, fast-paced, multi
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the Harvard University IT technical standards, policies and Code of Conduct Participate in off-hours on-call rotation Qualifications Basic Qualifications: Minimum of five years’ post-secondary education or
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. Demonstrated experience implementing, training, evaluating, or fine-tuning modern machine learning models. Strong programming skills in Python and experience building and maintaining research code. Demonstrated
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. Demonstrated experience implementing, training, evaluating, or fine-tuning modern machine learning models. Strong programming skills in Python and experience building and maintaining research code. Demonstrated