IPL is expanding opportunities for hands-on training in problem-focused, policy-relevant social science research at Stanford. Apply now!
The IPL Collaborative Research Fellowship at Stanford University is a summer experiential training program that offers outstanding doctoral students the opportunity to actively participate in research projects with close advising and mentorship from IPL faculty and staff. Supported by Stanford’s Vice Provost of Graduate Education, the fellowship allows students to learn and participate in the full scope of the social science research process: research design, grant writing, data analysis, article composition, journal submission, response to reviewers, and publication-related outreach. Fellows may propose a specific project of interest or opt to be matched to existing IPL projects, working in a close-knit team with continual intellectual interaction between faculty, post-docs, and fellow graduate students. In addition, fellows participate in regular training seminars conducted by faculty, staff, postdocs, and former fellows on a variety of topics. Fellows often have an article or multiple articles emerge from this innovative summer program, and they have the opportunity to continue collaborating with the IPL during the academic year.
Past fellows’ accomplishments include:
- Publication in Science
- Publication in Proceedings of the National Academy of Sciences
- Co-PI status on a $150,000 grant
- Completion of a nationally representative survey experiment on attitudes toward refugees in Jordan
Past fellows have worked on a number of innovative IPL projects, including:
- Developing a matching algorithm to improve employment outcomes for refugees and asylum-seekers
- Scalable messaging and framing to reduce anti-immigrant sentiment in the United States
- Using data and human-centered design techniques to restructure refugee resettlement in collaboration with one of the world’s leading resettlement agencies, the International Rescue Committee
Training Seminars
Throughout the summer, IPL faculty, staff, postdocs, and advanced graduate students offer training seminars to the Stanford community. Topics will likely include:
- Coding in Teams: Best practices for collaborative data analysis
- Project management fundamentals
- Advanced Qualtrics Applications: Offline App and Conjoint Experiments
- Immigration Research, Technology and Ethics
- How to Train Enumerators
- Bridging the Gap: Applied Social Science and Theory
- Making Science Make Sense: Communicating Research to the Public and Policymakers
- Publishing Process: How to publish in general interest journals (i.e., Science, PNAS,) and field implications
Fellowship Terms
The IPL Collaborative Research Fellowship is a part-time summer experiential training program. Fellows are required to complete the equivalent of one month of full-time research throughout the entire summer, but they will have a flexible schedule to accommodate their own independent projects, travel, and/or field work. Fellows doing field work will be required to check in weekly with a faculty or staff member. Regular attendance at weekly lab meetings and training seminars is required throughout the summer. Fellows will also give a presentation in the fall describing their research and results. Fellows receive a stipend of $3,500 for the summer, and up to $1,000 per fellow is available in research funds to support pilot projects.
Eligibility
Applicants must be a currently enrolled doctoral student in any of Stanford University’s seven schools. They must have taken a minimum of two quantitative statistics courses, be familiar with causal inference, and have an interest in immigration policy. First- and second-year students are particularly encouraged to apply.
How to Apply
Complete the brief online application here.
Deadline: Applications must be submitted by April 26th, 2019. IPL Collaborative Research Fellows will be announced by May 10th, 2019.
Please contact IPL’s Executive Director, Duncan Lawrence (dlawrenc@stanford.edu), with any questions (Subject: IPL Summer Fellowship).
