Research Scientist, Legal Innovation through Frontier Technology Lab (liftlab), Stanford Law School

Budgeted Salary Range Upon Hire at the Law School:  $117,000-$130,000 annual base salary.

Stanford’s liftlab seeks to increase access to high quality legal services in the private sector by leveraging artificial intelligence (AI) and other frontier technologies. We design, investigate and evaluate AI tools in legal education and private practice that are aimed to both reduce the cost and increase the quality of legal services in a sustainable and responsible way. To bridge the gap between theory and practice, our work extends beyond conceptualization and encompasses the building of prototypes that help explore the utility of AI-based solutions. We are currently seeking a Research Scientist to join our team who will report directly to the Lab Directors.

As a Research Scientist you will:

• In partnership with the Directors and other staff, execute and administer research activities on AI and other legal technological developments; make recommendations on project development and implementation.
• Train classifiers, design/construct the architecture of AI platforms, build large language models (LLM) agents
• Oversee and support training of research assistants and student fellows on best practices and technical skills.
• Write and edit content for a variety of work product outputs, including peer-reviewed journal articles, white papers, project proposals, etc. Assist with the development of research grants, (i.e., may suggest new funding opportunities, write portions of grants, and/or summarize data for grant support).
• Represent the Lab and the specific projects for which the Research Scientist is responsible or is assisting in leading as the key contact and subject matter expert and develop communications for internal and external constituencies.
• Organize and/or participate in outreach activities such as events, partnerships, training, and conferences.
• May assist in the teaching and administration of courses at the intersection of AI & Law.
• Create and/or advise in the development of curriculum. Make recommendations for course improvements.

 

CORE DUTIES:

• Leveraging state-of-the-art large language models, administer research activities.
• Evaluate and develop new of modifications of usable data from complex data sources.
• Assess and produce relevant, standard, or custom information from structured data sources by querying data repositories and generating the associated information.
• Devise methods for identifying patterns and trends in valuable sources using software engineering principles and strong knowledge of at least programming language, such as Python or R; basic statistical ability. Determine and recommend additional data collection and reporting requirements.
• Design and disseminate reports, academic articles and law reviews to contribute to the body of emerging scholarship in the space of law and AI.
• Provide technical direction to other research staff and students.
• Identify and select usable data from subtle and complex data patterns to find ways to train LLMs on experiential knowledge. Use principles of engineering and related fields (linguistics, data science, natural sciences, statistics, etc.),
• Design methods to validate data to ensure high-quality output.
• Evaluate existing tools and develop new prototypes of technological solutions to legal problems to ensure research translates into meaningful improvements in legal service accessibility and quality.
   

Nice to Have:

• Interest in the causal inference and social sciences, particularly law (although the relevant legal knowledge can be obtained on the job)

This position will be a two-year fixed-term appointment, subject to renewal.

To be considered, please submit the following items along with your online application:

• CV
• Include as part of your cover letter, project and code samples or GitHub
• You may be asked to provide your transcript

Core Duties:

• Evaluate and develop new or modifications of usable data from complex data sources. Assess and produce relevant, standard, or custom information (reports, charts, graphs, and tables) from structured data sources by querying data repositories and generating the associated information.

• Devise methods for identifying patterns and trends in available information sources using a variety of qualitative and quantitative techniques. Determine and recommend additional data collection and reporting requirements. 

• Design and customize reports based      on data in the database. Distribute and disseminate reports to applicable agencies, researchers, management, and other internal end-users.                  

• Create non-routine databases and generate related information summaries.

•  Perform statistical analyses appropriate to complex data and reporting requirements.

• Serve as a resource for non-routine inquiries such as requests for statistics or surveys.

• Lead the implementation of data standards and common data elements for data collection.

• Collaborate with technical staff to standardize and systemize routine reports, dashboards, and metrics.

• May test prototype software and participate in the approval and release process for new software.

Minimum Education:

Bachelor’s degree.

Minimum Experience:

Three years of relevant experience or combination of education and relevant experience. Experience in a quantitative discipline such as economics, finance, statistics, or engineering.

Knowledge, Skills and Abilities:

• In-depth knowledge and experience using and applying analytical software, database management system software, database reporting software, database user interface and query software, and data mining software.

• Demonstrated ability to collect data using a variety of methods, such as data mining and hardcopy or electronic documentation study, to improve or expand databases.

• Intermediate statistical ability.

• Strong listening, verbal, and written communication skills.

• Ability to manage multiple activities in a deadline-oriented environment; highly organized, flexible, and rigorous attention to detail.

• Ability to use logic to calculate data; efficiently construct a database or scrutinize the form of a question.

• Ability to work with data of varying levels of quality and validity.

• Demonstrated ability to produce data in a clear and understandable manner meeting user requirements.

• Ability to work effectively with multiple internal and external customers.

• Ability to take a leadership role on projects and with users/clients.