Research Fellow, Regulation, Evaluation, and Governance Lab (RegLab) , Stanford Law School

📁
Academic
📅
104738 Requisition #

 The Regulation, Evaluation, and Governance Lab (RegLab) at Stanford University is hiring full-time pre-doctoral Research Fellows to join our research team. This is a minimum one-year position, with the option of renewal. 

This position is a great next step for those considering graduate school, law school, and/or business school in the future. Prior Research Fellows have been accepted by PhD programs in computer science, economics, and political science and JD programs at top schools (e.g., Harvard, Stanford, Princeton, Yale). In recent years, fellows have been coauthors on RegLab publications for PNAS, JAMA Health Forum, Nature Sustainability, the American Economic Journal: Economic Policy, the American Law and Economics Review, the Journal of Law, Economics, and Organization, ACM FAccT, the Journal of Empirical Legal Studies, and the Stanford Law Review

About Us: Stanford RegLab is an impact lab that partners with government and nonprofits to use machine learning and data science to modernize the public sector. We are an interdisciplinary team of data scientists, social scientists, engineers, and lawyers who are passionate about building high-impact demonstration projects for the future of governance. Some of our partners include the Environmental Protection Agency (EPA), the Internal Revenue  Service (IRS), the Department of Labor (DOL), and various public interest organizations. 

As a member of our research team, you will:

  • Work closely with the Faculty Director, Research Director/Manager, data scientists, and teams of fellows and students to drive forward a diverse research program focused on machine learning and policy evaluation
  • Conceptualize suitable empirical methodologies and models
  • Collect, manage, and structure quantitative datasets
  • Conduct statistical analyses of complex datasets and interpretation of results
  • Write reports Report writing and manuscript preparation
  • Design and implement state-of-the-art machine learning models, algorithms, and statistical models, while leading the collection of new data and the refinement of existing data sources. 
  • Have the opportunity to receive co-authorship on research papers

Qualifications:

  • A Bachelor's or Master’s degree in a relevant quantitative field (e.g., computer science, data science, statistics, engineering, mathematics, economics, or a related field)
  • Outstanding academic credentials and intellectual creativity
  • Eagerness to take initiative and solve intricate problems
  • Excellent time-management skills and ability to work effectively with minimal supervision
  • Exceptional research, analytical writing, and communication skills
  • Programming experience in R, Python, Stata, SAS, and/or other languages
  • Prior research experience and coursework in the empirical social sciences is preferred, but not required
  • Self-guided, self-learner, and engaged in the mission of the Lab
  • Experience working with machine learning frameworks (TensorFlow, TF, PyTorch, Scikit Learn, etc.), NLP, computer vision, or related fields is a plus

Application Instructions:

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

  • CV
  • Transcript(s) (unofficial is fine; please include all full-time programs)
  • Project/code samples or Github

There will be two rounds of application review. The deadline for the first round is: 7AM PDT December 2, 2024. The deadline for the second round: 7AM PST Jan 6, 2025. Applications will be evaluated on a rolling basis and preference will be given to first-round applicants.

**The expected pay for this position is $67,000 per annum. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. 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, and external market pay for comparable jobs. 

Salary and Benefits: Salary is competitive. Stanford provides excellent retirement plans, time-off, and family care resources, which you can read more about here: https://cardinalatwork.stanford.edu/benefits-rewards

*Note: 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.

My Submissions

Track your opportunities.

My Submissions

Similar Listings

School of Law, Stanford, California, United States

📁 Academic

School of Law, Stanford, California, United States

📁 Academic

School of Law, Stanford, California, United States

📁 Academic

Global Impact
We believe in having a global impact

Climate and Sustainability

Stanford's deep commitment to sustainability practices has earned us a Platinum rating and inspired a new school aimed at tackling climate change.

Medical Innovations

Stanford's Innovative Medicines Accelerator is currently focused entirely on helping faculty generate and test new medicines that can slow the spread of COVID-19.

Technology

From Google and PayPal to Netflix and Snapchat, Stanford has housed some of the most celebrated innovations in Silicon Valley.

Advancing Education

Through rigorous research, model training programs and partnerships with educators worldwide, Stanford is pursuing equitable, accessible and effective learning for all.

Working Here
We believe you matter as much as the work

Group Dance Class In A Gym
Nora Cata Portrait

I love that Stanford is supportive of learning, and as an education institution, that pursuit of knowledge extends to staff members through professional development, wellness, financial planning and staff affinity groups.

Nora Cata

School of Engineering

Students Working With A Robot Arm
Philip Cheng Portrait

I get to apply my real-world experiences in a setting that welcomes diversity in thinking and offers support in applying new methods. In my short time at Stanford, I've been able to streamline processes that provide better and faster information to our students.

Phillip Cheng

Office of the Vice Provost for Student Affairs

Students Working With A Robot Arm
Denisha Clark Portrait

Besides its contributions to science, health, and medicine, Stanford is also the home of pioneers across disciplines. Joining Stanford has been a great way to contribute to our society by supporting emerging leaders.

Denisha Clark

School of Medicine

Students Working With A Robot Arm
Laura Lind Portrait

I like working in a place where ideas matter. Working at Stanford means being part of a vibrant, international culture in addition to getting to do meaningful work.

Laura Lind

Office of the President and Provost

Getting Started
We believe that you can love your job

Join Stanford in shaping a better tomorrow for your community, humanity and the planet we call home.

  • 4.2 Review Ratings
  • 81% Recommend to a Friend

View All Jobs