Postdoctoral Research Associate - Print & Probability Project - Dietrich College

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Pittsburgh, PA Until 8/21/2026 H-1B sponsor history First posted January 22, 2026 Last posted January 22, 2026
Job description

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.

Core 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

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.

Base Qualifications

  • 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)

Strongly Preferred Qualifications

  • 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.

Joining the CMU team opens the door to an array of exceptional 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.

At Carnegie Mellon, we value the whole package when extending offers of employment. Beyond credentials, we evaluate the role and responsibilities, your valuable work experience, and the knowledge gained through education and training. We appreciate your unique skills and the perspective you bring. Your journey with us is about more than just a job; it’s about finding the perfect fit for your professional growth and personal aspirations.

Are you interested in an exciting opportunity with an exceptional organization?! Apply today!

Location

Pittsburgh, PA

Job Function

Pre/Post-Doctoral Associates & Fellows

Position Type

Postdoctoral Associate / Fellow (Fixed Term)

Full Time/Part time

Full time

Pay Basis

Salary

More Information: 

  • Please visit Why Carnegie Mellonto learn more about becoming part of an institution inspiring innovations that change the world. 

  • Click here to view a listing of employee benefits

  • Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran

  • Statement of Assurance

About this role

Summary

Develop AI methods for historical book analysis, integrating language models and computer vision.

Job title

Postdoctoral Research Associate - Print & Probability Project

Experience level

PhD

Industry

education

Location requirements

Pittsburgh, PA; remote work not specified

Salary

Not specified

Visa sponsorship

H-1B sponsor history

Management role

No

Skills & keywords

Required skills

large language modelsPythonPyTorchTensorFlowunstructured data

Preferred skills

early modern European historyarchival researchcomputer visionmultilingual

Specializations

AIlarge language modelscomputer visiondigital humanities
Locations

Structured locations inferred from the posting.

Pittsburgh, PA, USA

On-site City