Embedded Files
About Us
About Us
The Behavioral Economics and Decision-making Lab (BEDLab) conducts research at the University of California, Riverside at the intersection of behavioral economics, consumer psychology, and organizational behavior, with a particular emphasis on consumer and managerial decision making.
BEDLab is directed by Ye Li (Associate Professor of Management). BEDLab members include faculty associates Michael Haselhuhn (Associate Professor of Management) and Mindy Truong (Assistant Professor of Management), PhD students, and undergraduate/graduate research assistants, all of whom share an interest in using the tools of behavioral science to better understand and help human behaviors, especially consumer and organizational ones. Research assistants start by helping with faculty research and a select few eventually go on to be Research Associates leading their own independent research projects.
Research Opportunities - Open for new apps as of Summer 2025
Research Opportunities - Open for new apps as of Summer 2025
If you are interested in joining BEDLab as a research assistant (RA) and have at least a 3.5 GPA, please fill out the application form here: BEDLab application. We accept applications on a rolling basis, but preference is given to students who 1) are interested a career in academia (i.e., in pursuing a PhD), 2) have interest in behavioral science/behavioral economics/decision making, and 3) have more time left at UCR (i.e., not graduating soon). Honors students seeking a capstone mentor are also welcome.
RAs are expected to be available to do 3-6+ hours of work per week (although most weeks will be less) and to attend a 1hr weekly lab meeting (currently Thursday afternoons 3:30-4:30 in the School of Business Building). Responsibilities include collecting survey data, coding qualitative data, and providing feedback on experimental designs and results.
In addition to students who have an interest in our research topics, we also have a few openings for RAs with strong data analysis skills (majoring in business analytics, statistics, data science, actuarial science, etc.) to help analyze experimental data and work on projects using Natural Language Processing and Machine Learning techniques.
Page updated
Report abuse