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modern machine learning models Strong programming skills in Python and experience building and maintaining research code Demonstrated ability to use modern AI-assisted and agentic coding tools effectively
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experience building and maintaining research code Demonstrated ability to use modern AI-assisted and agentic coding tools effectively, such as Claude Code, Codex, or similar systems, in research and
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contributions Demonstrated experience implementing, training, evaluating, or fine-tuning modern machine learning models Strong programming skills in Python and experience building and maintaining research code
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to, the following: Data Analysis and Programming Develop study questions and analytic approach (including literature searches and data searches using various sources) Optimize, test, and debug model code Clearly
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-assisted approaches to biological data curation, including the use of large language models and AI coding assistants to accelerate and enhance curation tasks. Job-Specific Responsibilities: Reading and
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learning and information theory, and expertise in at least one of the following areas is preferred: AI alignment, (differential) privacy, and coding or information theory for AI systems. Proficiency in
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hours/week) 3. Communicate with families in order to recruit and schedule research participants. 4. Record and/or code data according to project requirements and established protocols. Training will
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Eligibility: Applicants must hold an active grant in one of the activity codes listed below, and the research proposed in the supplement must be accomplished within the competitive segment of the active award
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practices, industry standards, codes/jurisdictional authorities, and University guidelines/practices. Must maintain work area, tools and equipment in accordance with University standards/practices. Required
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to, the following: Data Analysis and Programming Develop study questions and analytic approach (including literature searches and data searches using various sources) Optimize, test, and debug model code Clearly