Postdoctoral Research Associate - Print & Probability Project - Dietrich College

Carnegie Mellon University • Pittsburgh, PA

21h

About The Position

Carnegie Mellon University is a private, global research university that challenges the curious and hardworking to deliver work that matters. Our outstanding institution has distinctive areas of excellence and a culture marked by ambition and a deep, practical engagement with challenges facing society. We continue to produce versatile alumni and draw faculty and staff eager to be a part of the university’s creative, dedicated and close-knit community. We place emphasis on practical problem solving, interdisciplinary learning, a transformative spirit, and collaboration From creative writing to statistics and data science, behavioral economics to social and political history, Dietrich College is home to 11 humanities and sciences departments, programs and institutes. Our world-class faculty and students work across areas to investigate and solve real-world problems. The Print & Probability project seeks a Postdoctoral Research Associate to develop AI methods for identifying printers of anonymous early modern books (1450-1800). Building on successful prior work that's identified clandestine printers of famous works such as Milton's Areopagitica, Hobbes' Leviathan, Locke's Two Treatises and Spinoza's Theological-Political Treatise, this Schmidt Sciences-funded phase integrates large language models with computer vision to systematically uncover hidden networks of controversial printing during censorship. Flexibility, excellence, and passion are vital qualities within the Dietrich College. Collaboration and cultural sensitivity are valued competencies at CMU. Therefore, we are in search of a team member who can effectively interact with a varied population of internal and external partners at a high level of integrity. We are looking for someone who shares our values and who will support the mission of the university through their work.

Requirements

• PhD in Computer Science, Computational Linguistics, Digital Humanities, Computational Cultural Studies, History, or related field
• Demonstrated expertise with large language models (fine-tuning, prompting, deployment)
• Strong Python programming with deep learning frameworks (PyTorch, TensorFlow)
• Experience with unstructured historical data (text extraction, entity resolution, knowledge graphs)
• Excellent communication skills and commitment to interdisciplinary collaboration
• Evidence of scholarly productivity (publications, presentations, software)

Nice To Haves

• Knowledge of early modern European history (1450-1800) or book history
• Experience with historical bibliography or archival research
• Familiarity with computer vision for document analysis
• Multilingual reading ability (e.g., English, Latin, French, Spanish, Italian, Dutch)
• Publication record in digital humanities or computational social science
• A combination of education and proven experience from which comparable knowledge is demonstrated may be considered.

Responsibilities

• Develop LLM-driven knowledge graphs that construct probabilistic historical priors from bibliographic records, trial transcripts, censorship lists, and apprenticeship data
• Design agentic frameworks using In-Context Learning and Chain-of-Thought prompting for transparent historical inference
• Develop Historical Hypotheses in collaboration with (other) expert humanists and book historians
• Integrate top-down LLM hypotheses with established bottom-up vision pipeline (existing: dhSegment/Eynollah line extraction, damage detection models, 280M+ character image database)
• Assist in original research on clandestine printing networks using computational tools
• Contribute to publications in both AI and humanities venues (machine learning conferences and book history journals)
• Contribute to open-source tools and datasets for the research community

Benefits

• Benefits eligible employees enjoy a wide array of benefits including comprehensive medical, prescription, dental, and vision insurance as well as a generous retirement savings program with employer contributions.
• Unlock your potential with tuition benefits, take well-deserved breaks with ample paid time off and observed holidays, and rest easy with life and accidental death and disability insurance.
• Additional perks include a free Pittsburgh Regional Transit bus pass, access to our Family Concierge Team to help navigate childcare needs, fitness center access, and much more!
• For a comprehensive overview of the benefits available, explore our Benefits page.

What This Job Offers

• Job Type: Full-time
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees