Research Fellowship in Law & Natural Language Processing

Overview

Julian Nyarko is a 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

Responsibilities

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

Conditions

The full-time position is intended for a duration of two years. 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 salary for this position is $67,000. Stanford University has provided a pay range 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.

Qualifications

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 2025.

The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned.

Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of the job.

Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

Stanford Law School seeks to hire the best talent and to promote a safe and secure environment for all members of the university community and its property. To that end, new staff hires must successfully pass a background check prior to starting work at Stanford University.