Postdoctoral Fellow in Quantitative Social Science

The Laboratory for Innovation Science at Harvard University (LISH) is accepting applications for postdoctoral fellowships in quantitative social science (economics, management, psychology and sociology) to facilitate research analyzing the diffusion, criticality, and economic impact of free and open source software (FOSS). LISH, in partnership with the Linux Foundation, works with companies, organizations, and communities involved in the open source ecosystem to determine how to better understand the current state of FOSS in order to foster greater security and sustainability. Candidates with a background in statistical analysis - particularly working with 'messy' data – as well as survey design and execution would be well-suited for this position. Prior experience working with or contributing to open source projects would be desirable, but is not required.

The Postdoctoral Fellow in Quantitative Social Science will be a member of the team that works with the Linux Foundation to analyze data collected from various partners, including private companies, public sources, and surveys of the open source community. As such, the fellow will apply computational techniques to analyze various datasets, including, - but not limited to – relevant public data and project metrics via data mining and APIs, as well as aggregating private datasets from source code analysis audits and scans. Data analysis will focus on identifying critical open source projects and security-related trends. The fellow will also design and conduct large-scale surveys of open source contributors and end-users on the use of and security practices surrounding open source projects.

The Postdoctoral Fellow will work under the supervision of LISH Directors and affiliated faculty and will have the opportunity to collaborate with LISH staff, postdoctoral fellows, and doctoral students. LISH is a Harvard-wide research program led by faculty co-directors Karim Lakhani and Marco Iansiti, 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, Linux Foundation, Topcoder, Kaggle, and other firms). Current research topics for the lab include governance and management of open innovation systems, like the open source community.

Select candidates may be required to take a short assessment test.

Basic Qualifications:

  • Ph.D. in economics, management, psychology, sociology, or another related quantitative social science field.

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 or will be conferred. No exceptions.

Additional Qualifications:

  • Experience writing, designing, executing, and analyzing surveys using an online survey platform (e.g., Qualtrics).
  • Experience with statistical analysis, particularly working with 'messy' data -- identifying missing data, matching heterogeneous data sources using fuzzy matching techniques, etc.
  • Experience querying databases/web APIs and using statistical computer languages: R, Python, etc.
  • Practical knowledge of analytics, computation, data analysis software (e.g., R, STATA, SPSS, SAS, etc.)
  • Ability to handle multiple projects, stakeholders, and demands
  • Strong team player with excellent verbal and written communication skills
  • Interest in learning about the open source ecosystem, including the economic impact and security of open source projects

Responsibilities:

  • Collect, aggregate, and prepare the data on the usage, sustainability and criticality of open source projects;
  • Design, launch, and analyze large-scale survey of open source contributors;
  • Create, enhance, and maintain documentation for data, analytic choices, rationale, and results;
  • Provide weekly updates on data collection, aggregation, and analysis to internal and external collaborators;
  • Document and disseminate findings through publication of white papers, partner reports, and academic publications.

Appointment Details:

This position is funded by an award administered by the Institute for Quantitative Social Science (IQSS) at Harvard.

This is a one-year term appointment through Harvard University with the possibility of renewal based on performance and funding.

Incumbent will work remotely based on Harvard University’s COVID-19 response policy until further notice. Work must be performed within the US. Individuals who are located in the US may work outside of Massachusetts (MA) until 90 days after the MA COVID-19 state of emergency is no longer in effect. Individuals located in the US working outside of MA must acknowledge to Harvard in writing that after the interim pandemic policy ends, the employee must relocate to MA and their campus work location.

Employees will have federal and MA state taxes withheld.

We are unable to provide visa sponsorship for this position.

Application Process:

The application deadline is June 15, 2021.  Please email the following items to lish@harvard.edu:

  • Curriculum Vitae
  • Copy of academic records (unofficial records are acceptable)
  • A two-page description of relevant experience with algorithms and data analysis
  • Two recently published or working papers
  • Contact details of two references