Research Intern - Inference Economics and Human Agency

Research Interns put inquiry and theory into practice. Alongside fellow doctoral candidates and some of the world's best researchers, Research Interns learn, collaborate, and network for life. Research Interns not only advance their own careers, but they also contribute to exciting research and development strides. During the 12-week internship, Research Interns are paired with mentors and expected to collaborate with other Research Interns and researchers, present findings, and contribute to the vibrant life of the community. Research internships are available in all areas of research, and are offered year-round, though they typically begin in the summer. Currently enrolled in a PhD program in Computer Science, Cognitive Science, Human-Computer Interaction, Information Systems, Behavioral Economics, or a related STEM field. At least 1 year of research experience in one or more of the following: human-AI interaction, decision science, metacognition, AI/LLM evaluation, or computational economics. In addition to the qualifications below, you'll need to submit a minimum of two reference letters for this position as well as a cover letter and any relevant work or research samples. After you submit your application, a request for letters may be sent to your list of references on your behalf. Note that reference letters cannot be requested until after you have submitted your application, and furthermore, that they might not be automatically requested for all candidates. You may wish to alert your letter writers in advance, so they will be ready to submit your letter. Experience designing and running human-subjects experiments (IRB-compliant protocols, participant recruitment, controlled task studies). Familiarity with LLM agent architectures, prompt engineering, or multi-step AI orchestration systems. Background in confidence calibration, signal detection theory, or metacognitive measurement. Experience with mixed-methods research combining quantitative behavioral data and qualitative interview analysis. Proficiency in Python and statistical analysis tools (R, pandas, scipy, or equivalent). Published or in-progress research in CHI, CSCW, FAccT, AAAI, NeurIPS, or related venues. Familiarity with inference cost modeling, token economics, or cloud compute pricing.

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