Job Summary

Purdue University invites applications for a Postdoctoral Scholar to join a Sloan Foundation–funded research project led by Prof. Eamon Duede. The project investigates how the rapid emergence of artificial intelligence (particularly large language models) is reshaping epistemic norms and practices across the sciences. This is a one-year FY position beginning August 2026 to August 2027.

Unlike previous domain-specific technologies, contemporary AI systems are domain-general, capable of participating in nearly every stage of inquiry. This project aims to provide conceptual and empirical clarity on how these systems influence the standards of justification, proof, problem selection, and collaboration that shape the life of scientific disciplines. One core empirical focus will be on formal mathematics and the Lean open-source mathematics community, which offers rich, structured data for studying norm evolution in real time. Comparative work across disciplines will complement these analyses.

This postdoc will have the opportunity to work at the intersection of Science, Philosophy of Science, STS, and AI as part of an interdisciplinary team spanning Purdue University and Argonne National Laboratory, with collaborations at Frontier AI labs, Carnegie Mellon, the University of Chicago, Duke University, Princeton University, and others. The successful candidate will play a central role in advancing empirical and conceptual understanding of how emerging AI systems reshape the epistemic norms and practices of scientific inquiry. This position provides close mentorship, collaboration with leading research groups, opportunities for travel to workshops and conferences, and a strong platform for launching an independent academic career focused on AI and the future of scientific practice.

Responsibilities

• Build and maintain computational data pipelines to collect and structure evidence from scientific communities (e.g., GitHub repositories, communication forums, project documentation).
• Drive analysis of evolving epistemic practices, including proof and justification styles, problem selection, and collaboration norms as AI tools are integrated into research workflows.
• Construct and analyze dependency and contribution networks to identify structural changes in inquiry.
• Combine quantitative analyses (e.g., network and hypergraph models) with qualitative discourse analysis to link community debates to observed behavioral changes.
• Co-author and present scholarly publications and collaborate with external partners.

Education

 Required Qualifications

• PhD in one of the Computational Social Sciences, Science of Science, Science and Technology Studies, Philosophy of Science, Sociology of Science, Mathematics, Computer Science, or a closely related field.
• Demonstrated computational expertise (e.g., Python, network analysis, data wrangling).
• A research profile that engages with questions at the intersection of AI, scientific practice, and epistemology.
• Excellent writing and communication skills.

Preferred Qualifications

• Experience with formal or computational representations of scientific reasoning (e.g., proof assistants, simulation frameworks, structured data environments).
• Familiarity with Lean or other formal mathematics platforms.
• Experience with temporal network analysis or hypergraph modeling.
• Background in interdisciplinary research teams.

Application Instructions 

Please submit: :

1. A cover letter describing your research interests and fit for the project.
2. Curriculum vitae.
3. One or two writing samples (published or in-progress).
4. Names and contact information for 2–3 references.

Applcations will be reviewed on a rolling basis beginning February 15, 2026. For full consideration, apply by February 23, 2026. A background check is required for employment in this position.

Purdue University is an EOE/AA employer. All individuals, including minorities, women, individuals with disabilities, and veterans are encouraged to apply.