Research Fellowship in Law & Natural Language Processing


Julian Nyarko is an associate professor at Stanford Law School who applies tools from natural language processing and machine learning to legal research questions. This full-time research fellowship provides opportunities to assist Professor Nyarko in his research. The fellowship is aimed at recent graduates who are considering entering a graduate degree program (Ph.D. / JD) in the near future. The inaugural fellow began a Ph.D. at MIT after the fellowship.

Examples of Current Projects

  • Development of methodology and best practices to employ language models for hypothesis testing in the social sciences
  • Legal document parsing and segmentation
  • Unsupervised identification of novel legal ideas and concepts
  • Assessment of overreporting on minority suspects in crime reports issued by the police via social media


Specific responsibilities can vary over time, but generally include:

  • Conceptualization and implementation of statistical models
  • Collecting, managing, and structuring quantitative datasets
  • Report writing and manuscript preparation


The full-time position starts in Summer 2023 is intended for a duration of two year. It is expected that the fellow will be physically present in and working from Stanford Law School. As full-time Stanford University employees, fellows will receive a competitive salary and benefits package, including medical, dental, and vision insurance, access to campus athletic and academic facilities, paid vacation time, professional development funds, and the capacity to audit Stanford courses and attend on-campus lectures and seminars free of charge.

The expected base pay for this position is $64,480.

Stanford University has provided this base pay amount representing its good faith estimate of what the university reasonably expects to pay for the position. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the qualifications of the selected candidate, budget availability, and internal equity.


Experience and knowledge of the following is required:

  • A Bachelor’s degree in a relevant field
  • Experience with statistics
  • Programming experience
  • Ability to work under deadlines with general guidance

Experience and knowledge of the following is highly desirable:

  • A Bachelor’s degree in computer science with a background in NLP, a Bachelor’s degree in (computational) linguistics or in symbolic systems
  • A strong, demonstrated interest to conduct academic research in a relevant field
  • Interest in legal research
  • Interest in causal inference and social science
  • Experience with machine learning / deep learning
  • Substantial experience with Python
  • Substantial experience with R

How to Apply

All positions are currently filled. Please check back again in early 2024.