Note:
The expected pay range for this position at Stanford Law School is $29.52 to $34.13 per hour. Stanford University provides pay ranges representing its good faith estimate of the hourly wage the university reasonably expects to pay for a position upon hire. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs. At Stanford University, base pay represents only one aspect of the comprehensive rewards package.
The full-time position is fixed-term for one year, with the intention to renew for a second year, subject to approval. It is expected that the fellow will be physically present in and working from Stanford Law School.
This full-time research fellowship provides opportunities to assist the Legal Innovation through Frontier Technology Lab (liftlab), jointly led by Professor Julian Nyarko and Dr. Megan Ma, in its research. The Fellow will support the execution and administration of research activities on AI and other legal technological developments; and make recommendations on project development and implementation. The fellowship is aimed at recent graduates who are considering entering a graduate degree program (Ph.D. / JD) in the near future. The first two fellows have gone on to pursue PhDs at MIT and Harvard, respectively, as well as a JD at Stanford.
Examples of Current ProjectsImproving contract drafting practices by identifying litigation-triggering language
Developing a benchmark to compare rubrics and preference ranks as a method to elicit quality in high-judgment domains
Developing and experimentally testing LLM-based interventions to improve negotiation outcomes
LLM personalization to improve downstream outcomes
Large-scale evaluation of AI tutors for law
Developing a methodology to predict future innovations in the social sciences
Auditing and mitigation of bias in LLMs via pruning
Responsibilities:
Designing methods to validate data to ensure high quality output
Identifying new sources of data and methods to improve data collection, analysis and reporting
Conceptualization and implementation of statistical models
Collecting, managing, and structuring quantitative datasets
Report writing and manuscript preparation
Using LLM agents for the implementation and execution of research+
Preferred Qualifications:
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:
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
