The U.C. Berkeley Data-Intensive Development Lab explores how novel sources of data, and new computational algorithms, can provide insight into the causes and consequences of economic development. We are currently soliciting applications for postdocs, data scientists, and research associates, with appointment to begin in early 2020 (or possibly earlier).
The postdoc or research associate will work on interdisciplinary research challenges that lie at the intersection of development economics and statistical machine learning. Research activities will be supervised by Joshua Blumenstock (UC Berkeley School of Information), and will build on research topics including:
Depending on interest, you may work on existing collaborative projects with Sham Kakade (UW Computer Science), Jacob Shapiro (Princeton Politics and International Affairs), Moritz Hardt (UC Berkeley Computer Science), Dan Bjorkegren, and/or Solomon Hsiang (UC Berkeley Public Policy). Please refer to the lab and academic websites for examples of ongoing projects.
Qualified candidates should have a graduate degree in Computer Science, Economics, Statistics, or a related field. Strong technical, analytic, and computational skills are essential: all projects involve the analysis of large, complex data, and require proficiency in one or more object-oriented programming languages. Experience with applied machine learning and econometrics are desired.
Interested individuals should send the following materials to Joshua Blumenstock (firstname.lastname@example.org): a CV, a cover letter describing research interests and prior relevant experience, two writing samples, and three letters of reference (or the names of references, if letters are not available). Review of applications will begin on September 15, 2019.