Postdoctoral Research Associate Print & Probability Project Dietrich College

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profile Job Location:

Pittsburgh, PA - USA

profile Monthly Salary: Not Disclosed
Posted on: 11 hours ago
Vacancies: 1 Vacancy

Job Summary

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 universitys 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.

ThePrint & Probability projectseeks a Postdoctoral Research Associate to develop AI methods for identifying printers of anonymous early modern books (1450-1800). Building on successful prior work thats identified clandestine printers of famous works such as Miltons Areopagitica Hobbes Leviathan Lockes Two Treatises and Spinozas 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 graphsthat construct probabilistic historical priors from bibliographic records trial transcripts censorship lists and apprenticeship data
  • Design agentic frameworksusing In-Context Learning and Chain-of-Thought prompting for transparent historical inference
  • Develop Historical Hypothesesin 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 researchon 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 datasetsfor 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

  • PhDin 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 programmingwith deep learning frameworks (PyTorch TensorFlow)
  • Experience with unstructured historical data(text extraction entity resolution knowledge graphs)
  • Excellent communication skillsand 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; its 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

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Required Experience:

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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...
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  • Research Experience
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  • Molecular Biology
  • Microscopy
  • Research Laboratory Experience
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Carnegie Mellon University will have a transformative impact on society through continual innovation in education, research, creativity, and entrepreneurship. Our Mission To create a transformative educational experience for students focused on deep disciplinary knowledge, problem so ... View more

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