Stanford University-posted about 2 months ago
$34 - $40/Yr
Full-time • Entry Level
Hybrid • Stanford, CA
5,001-10,000 employees
Educational Services

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 based on performance and funding. 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. The following tasks are designed to culminate in co-authorship on research papers:

  • Plan and perform research tasks requiring initiative and judgment: conceptualize suitable empirical methodologies and models,
  • Collect, manage, and structure quantitative datasets,
  • Conduct statistical analyses of complex datasets and interpret results,
  • Design and implement state-of-the-art machine learning models, algorithms, and statistical models,
  • Participate in literature searches, report writing and manuscript preparation
  • Present research findings to supervisor.
  • Ensure compliance with research protocols.
  • You may be asked to orient and train new staff or students.
  • A Bachelor's degree in an applicable quantitative field (e.g., computer science, data science, statistics, engineering, mathematics, economics, or a related field), MS degree preferred.
  • Creativity
  • Ability to quickly learn in a new work environment
  • Eagerness to take initiative and solve intricate problems
  • Ability to work under deadlines with general guidance.
  • Exceptional research, analytical writing, and communication skills
  • Excellent organizational skills and demonstrated ability to complete detailed work accurately.
  • Programming experience in R, Python, Stata, SAS, and/or other languages
  • Self-guided, self-learner, and engaged in the mission of the Lab
  • Prior research experience and coursework in the empirical social sciences is preferred, but not required
  • Experience working with machine learning frameworks (TensorFlow, TF, PyTorch, Scikit Learn, etc.), NLP, computer vision, or related fields is a plus
  • At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website (https://cardinalatwork.stanford.edu/benefits-rewards) provides detailed information on Stanford's extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process.
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