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About the Opportunity Job Summary You will serve as the ground truth for AI validation by manually coding student simulation transcripts using detailed rubrics. This role requires meticulous
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statistical analyses, and coding in computer languages (SPSS, R, etc.) • Familiar with Microsoft Office suite and research databases such as RedCap. • Have excellent oral and written communication skills
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surveys; lead qualitative coding of interview and focus group data Maintain IRB protocols, data use agreements, and study documentation Lead drafting of annual research summaries, the final comprehensive
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of nonlinear finite element analysis and experience with commercial or open-source finite element codes, such as Abaqus, including user-defined material subroutines Ability to program in Python and develop
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of contracted work. Demonstrated experience developing budgets and preparing financial reports. Experience interpreting and applying applicable codes, regulations, and university policy in a facilities context as
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(e.g., Azure, AWS, or GovCloud equivalents), including containerized or scalable ML workflows. Solid software engineering fundamentals, including version control, modular code design, testing
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, and formal methods for the robustness, performance, correctness, and security of code generated by AI or interacting with AI. Areas of interest include the coordination and validation of concurrent AI
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institution or related organization. Has showcased experience in qualitative data methods, program evaluation, and assessment, with backgrounds in thematic coding and survey design strongly desired. Has
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recommendations. Automation & Infrastructure as Code (IaC): Define Infrastructure as Code (IaC) best practices using Terraform, Bicep, and ARM templates to automate cloud deployments. Oversee CI/CD integration
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can upload participants' written memory responses and receive automated scores in return, without writing any code. The platform is designed to host a range of scoring models (both the models we develop