A growing list of ways to engage on AI-related topics, pursue funding for AI research, and more.
Graduate Certificate in Brains, Minds, and Machines
To prepare the next generation of researchers, the Wu Tsai Center’s Graduate Certificate in Brains, Minds, and Machines equips PhD students at Yale with integrative training across biological, psychological, and computational approaches.
First-year graduate students from any PhD program in Yale’s Graduate School of Arts and Sciences are eligible to apply. The student’s current or planned dissertation advisor must be a Wu Tsai Faculty Member. Students are expected to include at least one additional Wu Tsai Faculty Member on their thesis committee once the committee is established.
2025-26 Application
March 16, 2026
Applications open
April 16, 2026
Applications close
June 2026
Selections announced
Fall 2026
Inaugural cohort begins certificate activities in their second year
Visit Graduate Certificate in Brains, Minds, and Machines for details and how to apply.
Please contact wti@yale.edu with questions.
Librarian for Computational Theology
The Yale Divinity Library seeks a librarian to advance the Divinity Library’s services related to artificial intelligence, emerging technologies, digital imaging, and digital preservation. This librarian will serve as a member of a team of subject specialists at the Divinity Library providing outreach to students and faculty. The Librarian for Computational Theology will also coordinate with functional specialists at the Divinity Library and across the University Library to assist with technical services workflows.
Postdoctoral Research Position — Topic: Acceleration of Cultural Heritage Provenance Research with AI — Cultural Heritage division
Understanding a collection item’s history, whether it is a painting in an art museum, a specimen in a natural history collection, or documents in an archive, is an essential part of responsible stewardship of that object. The research topic to be explored is the extent to which AI can accelerate provenance research processes, including especially the use of Large Language Model based transcription of printed and handwritten documents, and subsequent extraction of knowledge from the transcribed text as to the people, places, organizations and events in which the object participated.
Yale is uniquely positioned to support this research, with significant collections, art historical experts, technical expertise and connections to related endeavors and communities. The postdoc will have direct access to all of the expertise needed for the research to be successful, and can be embedded within museums or more technical parts of the University for periods of time to learn about both research and operational workflows.
Postdoctoral Research Position — Research Dataset Discovery with Knowledge Graphs and AI — Cultural Heritage division
Discovering relevant research datasets is a significant challenge due to inconsistent descriptive practices, the vast scale of research, and researchers’ limited time and expertise to adequately document their data. As a result, datasets are typically found through scholarly articles and professional networks, or via web search engines, rather than through any centralized or standardized discovery system.
At Yale, we envision a different future. This post-doctoral position will investigate the use of knowledge graphs on automatically extracted metadata at a cross-disciplinary global scale. Using LLMs and traditional data engineering techniques, we will discover, characterize, reconcile, enrich and connect the datasets with the subjects, people, institutions, places, research projects, and funding programs in order to facilitate both graph-based analysis of research data as a meta-domain and discovery of relevant datasets through both graph search and guided browsing through relationships.