Postdoctoral Research Fellow in Computational Linguistics and Language Acquisition

Applicants should submit the following as a single PDF through the University of Michigan job portal:

1. Cover letter describing qualifications, research interests, and fit
2. A CV
3. A research statement (up to 3 pages)
4. Up to three representative publications or manuscripts
5. Names and contact information for three recommenders

Position Start Date: August 15, 2026 (negotiable)

Specialty Areas: Computational Linguistics, Language Acquisition, Cognitive Modeling, Machine Learning

The Department of Linguistics at the University of Michigan invites applications for a one-year Postdoctoral Research Fellow, with the possibility of renewal for a second year, to work with Dr. Huteng Dai on computational modeling of language acquisition. The postdoc will play a central role in developing publishable research that connects formal inductive biases, modern language modeling, and human language acquisition.

We are especially interested in candidates who are excited to build and analyze language models that go beyond standard scaling approaches, including work such as:

• Inductive bias and learnability, especially structural biases rooted in formal language theory
• Computational models of language acquisition, especially building models for phonological and syntactic learning
• Mechanistic interpretability and controlled evaluation of language models
• Model human alignment, relating model behavior to behavioral (and potentially neural data) data

The overarching goal is to produce rigorous, high-impact work that treats language models as scientific objects.

The postdoctoral fellow will contribute across the full research cycle. Key responsibilities include:

• Designing and training novel or modified language models
• Building evaluation pipelines for acquisition-oriented questions
• Conducting interpretability analyses
• Co-authoring papers for high-impact refereed publications
• Mentoring and coordinating graduate and undergraduate researchers in the lab

Participating in regular lab meetings

Teaching: The postdoc may contribute to the departments course offerings. Teaching load may be up to two courses a year. Course assignment will be determined in consultation with the department and aligned with the fellows expertise and interests.

Required:

• Ph.D. in Linguistics, Computer Science, Cognitive Science, or a related field by the start date
• Strong background in computational linguistics or deep learning
• Demonstrated interest in at least one of: language learning/acquisition, interpretability/mechanistic analysis, human-like modeling, or formal language theory
• Excellent programming and data analysis skills (Python required; familiarity with PyTorch and Hugging Face strongly preferred)
• Strong communication and collaboration skills, with evidence of research productivity

Preferred:

• Experience with or interest in phonology, syntax, or language acquisition
• Familiarity with formal language theory or cognitive modeling
• Experience working with human behavioral data or an interest in doing so
• Interest in interdisciplinary research bridging linguistics and machine learning

The University of Michigan Linguistics Department offers a highly interdisciplinary environment with strong connections to Computer Science, Psychology, Philosophy, and the Weinberg Institute for Cognitive Science. The department and university provide substantial research infrastructure and an active community in computational linguistics and cognitive modeling.

Benefits information is available at: https://hr.umich.edu/benefits-wellness.

The University of Michigan is an equal opportunity and affirmative action employer. We are committed to creating an inclusive, equitable, and supportive environment in which to learn, teach, and conduct research. We encourage applications from candidates who will contribute to the diversity and excellence of our academic community.

For questions about the position, contact Ling.CAP.Lab@umich.edu

April 30, 2026 (applications will be reviewed on a rolling basis until the position is filled)