Economics/Management Post-Doctoral Fellowship

Cambridge, MA, USA
Jun 06, 2018
Jul 06, 2018
Contract Type
Full Time
Job Type
PhD / Doctoral

Economics/Management Post-Doctoral Fellowship

Faculty of Arts and Sciences

Institute for Quantitative Social Science (IQSS)

Position Description

The Laboratory for Innovation Science at Harvard University (LISH) is soliciting applications for one or more post-doctoral fellowships aimed towards quantitative and experimental social science (economics, management, psychology and sociology). LISH is a Harvard-wide research program lead by faculty co-directors Karim Lakhani, Harvard Business School; Eva Guinan, Harvard Medical School; and David Parkes, Harvard School of Engineering and Applied Sciences. LISH is an interdisciplinary research lab that is focused on developing a science of innovation through the application of quantitative and field experimental methods on innovation problems faced by our partners (NASA, Harvard Medical School, Broad Institute, Department of Defense Research Labs, TopCoder and various corporations).

The Post-Doctoral Fellow will work under the supervision of LISH Directors and affiliated faculty and will have the opportunity to collaborate with LISH staff, postdocs, and doctoral students. Current research topics for the lab include incentives for innovation, governance and management of innovation systems, and creativity and problem solving. The areas of application where we conduct our research include innovation contests and communities, science laboratories and R&D organizations, research funding and publishing, technology commercialization and transfer, and data science. Our work is primarily empirical; a typical project will involve: conceiving a suitable research question, designing a suitable field experiment, working with collaborating partners, analyzing historical data, analyzing experimental data and writing papers. Previous work has examined the motivations and incentives of crowdsourcing participants, the management of research laboratories, and citing behavior in academic literature.

The position has no teaching or administrative duties.

LISH is looking for candidates with diverse backgrounds and/or new perspectives.

This is a term appointment through 10/31/18, with the possibility of extension based on funding and performance.

Basic Qualifications

• A PhD in economics, management, psychology, sociology, computer science and or a related field is required. PLEASE NOTE: If you have obtained your Ph.D. in the past 12 months you must be able to provide a certificate of completion from the degree-granting institution OR a letter from the institute's registrar stating all requirements for the degree have been successfully completed and should verify the date the degree has been conferred. No exceptions.
• Experimental design: treatment selection, power analysis
• Game theoretic modeling of behavior
• Statistical analysis: panel data methods, linear and generalized linear regression
• Strong quantitative skills with proficiency in a suitable numerical analysis environment, e.g., MATLAB, R, or, Stata
• Programming/scripting knowledge suitable for processing raw data for analysis, e.g., text manipulation
• Strong team player with excellent communication skills

Additional Qualifications

Special Instructions

Applications will be accepted until the position is filled. Please email the following to Steven Randazzo at with subject "Post-Doctoral Fellowship":

• Curriculum vitae
• Copy of academic records (unofficial records are acceptable)
• 2-page description of relevant experience
• Job market paper or one or two research papers
• Provide at least two letters of recommendation

Contact Information

Steven Randazzo

Contact Email

Equal Opportunity Employer

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.

Minimum Number of References Required

Maximum Number of References Allowed

Supplemental Questions