Research Fellowship in Law & Natural Language Processing

Overview

Julian Nyarko is an assistant 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 will be moving on from this fellowship to begin a Ph.D. at MIT after this summer.

Examples of Current Projects

  • Development of methodology and best practices to employ word embedding 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 starts in Summer 2021 and is for approximately one year, with an option to renew for a second year by mutual agreement. If consistent with pandemic restrictions, 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.

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

The application for the fellowship is now closed. Please revisit this page in early Summer of 2022.