Research Fellowship in AI and the Law (liftlab) - Stanford Law School
Overview
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 Projects
- Improving contract drafting practices by identifying litigation-triggering language
- Large-scale evaluation of AI tutors for law
- Development of methodology and best practices to employ LLMs for hypothesis testing in the social sciences
- New methods to promote the interpretability of embedding vectors
- Unsupervised identification of novel legal ideas and concepts
- Data attribution at scale
- 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
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. As full-time Stanford University employees, fellows will receive a competitive salary and option to elect a benefits package, including medical, dental, and vision insurance, access to campus athletic and academic facilities, paid time off, 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
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