Open Positions

The Laboratory for Innovation Science at Harvard (LISH) is looking for an energetic Program Associate for the brand-new Open Source Software Initiative. Together with partners such as The Linux Foundation, the lab will establish a network of collaborators that will conduct research on the composition and practices of the open source software community.

LISH is looking for candidates with diverse backgrounds and/or new perspectives. This is a term position through 12/31/19, with the possibility of renewal based on funding and performance.

Duties will include:

• researching open source software, how it is currently used, its community and its users
• understanding OSS adoption of software package data exchange and code architecture
• coordinating the development of the network, including the supporting infrastructure and the identification and invitations to potential principle investigators and researchers at other academic institutions
• tracking deliverables and milestones on projects, as well as communicating with partners and funders
• crafting presentations based on research findings, writing literature reviews and briefs
• extraction, cleaning, exploration, and analysis of data collected from various sources, including organizational data and aggregated intelligence
• creation and maintenance of documentation of data files, modeling choices, rationale, and results
• creation of prediction and classification models using validated measurements/features
• working with the LISH Research Team to design and execute projects with partner research organizations

Basic Qualifications

• B.A. or B.S. in a relevant field with one to two years of relevant work experience
• Understanding of qualitative and quantitative research methods and software applications
• Experience managing large datasets

Additional Qualifications

• Strong project management skills
• Demonstrated knowledge in Microsoft Office Suites (including proficiency in Excel and PowerPoint)
• Previous work experience in an open source community and/or background knowledge of open source software

Additional Information

If interested in applying, please email the following to Jenny Hoffman, jhoffman@hbs.edu, with “Program Associate - OSSI” as the subject line:

• Curriculum vitae
• Copy of academic records (unofficial records are acceptable)
• 1-page cover letter highlighting relevant experience
• At least two letters of recommendation

You can find more information here after January 3rd. 

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. The Fellow will assist LISH faculty on a new NSF sponsored project aimed at understanding the impact of Autonomous Vehicles (AVs) on the productivity of knowledge workers. The tasks included in this project will range from the analysis to existing time-use data, to the design of new surveys and field experiments.

The position has no teaching or administrative duties.

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

This is a grant-funded position expected to last for three years with reappointments made annually.

Basic Qualifications

• Experimental design: treatment selection, power analysis
• 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

Applications will be accepted until the position is filled. Please email the following to Nina Cohodes, nina_cohodes@iq.harvard.edu with subject “NSF 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

See here for more information.