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Postdoctoral Research Associate - Print & Probability Project - Dietrich College
full-timePittsburgh

Summary

Location

Pittsburgh

Type

full-time

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About this role

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

Other facts

Tech stack
Large Language Models,Python Programming,Deep Learning,Historical Data,Text Extraction,Entity Resolution,Knowledge Graphs,Interdisciplinary Collaboration,Communication Skills,Historical Bibliography,Archival Research,Computer Vision,Document Analysis,Multilingual Reading,Digital Humanities,Computational Social Science

About Carnegie Mellon University

The Language Technologies Institute at the Carnegie Mellon University School of Computer Science educates the leaders of tomorrow and performs groundbreaking research in the areas of Natural Language Processing and Computational Linguistics; Information Extraction, Summarization & Question Answering; Information Retrieval, Text Mining & Analytics; Knowledge Representation, Reasoning & Acquisition; Language Technologies for Education; Machine Learning; Machine Translation; Multimodal Computing and Interaction; Speech Processing; and Spoken Interfaces & Dialogue Processing.

Team size: 51-200 employees
LinkedIn: Visit
Industry: Higher Education
Founding Year: 1986

What you'll do

  • The Postdoctoral Research Associate will develop AI methods for identifying printers of anonymous early modern books and assist in original research on clandestine printing networks. They will also contribute to publications in both AI and humanities venues.

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Frequently Asked Questions

What does a Postdoctoral Research Associate - Print & Probability Project - Dietrich College do at Carnegie Mellon University?

As a Postdoctoral Research Associate - Print & Probability Project - Dietrich College at Carnegie Mellon University, you will: the Postdoctoral Research Associate will develop AI methods for identifying printers of anonymous early modern books and assist in original research on clandestine printing networks. They will also contribute to publications in both AI and humanities venues..

Why join Carnegie Mellon University as a Postdoctoral Research Associate - Print & Probability Project - Dietrich College?

Carnegie Mellon University is a leading Higher Education company.

Is the Postdoctoral Research Associate - Print & Probability Project - Dietrich College position at Carnegie Mellon University remote?

The Postdoctoral Research Associate - Print & Probability Project - Dietrich College position at Carnegie Mellon University is based in Pittsburgh, Pennsylvania, United States. Contact the company through Clera for specific work arrangement details.

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