Research Associate
The OpenDP Project at Harvard University seeks to hire a Research Associate to work with faculty directors Gary King and Salil Vadhan and the OpenDP Community to formulate and advance the scientific goals of OpenDP and solve research problems that are needed for its success.
Candidates should have familiarity with differential privacy and one or both of the following:
- Experience with implementing software for data science, privacy, and/or security, and an interest in contributing to the development of the OpenDP codebase.
- Experience with applied statistics, and an interest in working with domain scientists to apply OpenDP software to data-sharing problems in their field.
Key responsibilities include:
- Working with the OpenDP team, our collaborators and community members on applying differential privacy in building software tools for data science problems
- Writing grant applications for fundraising and outreach
- Serving as the scientific point of contact and fulcrum with use case partners and DP subject matter experts.
It is expected that the research associate will regularly write and publish research papers related to their work with OpenDP. They will be free to spend up to 20% of their time on their own independent research projects, a percentage that can be increased if funding is raised to support such work.
Initial salary will be provided with the offer, with the expectation that the candidate will work with the OpenDP team to raise funding for future support.
Candidates are required to have a PhD and at least three years of postdoctoral experience. We strongly encourage applications from historically underrepresented groups. Candidates whose profile does not exactly fit the posting (e.g. being more junior or more senior) should still reach out to us and apply; we may be able to tailor the position to fit.
Required application materials include a cover letter; an updated curriculum vitae; a two-to-four page statement on research and applications discussing both past accomplishments and current and future areas of interest; links to at most three research papers or software products. Please submit the names and contact information for three references.
Applications will be reviewed on a rolling basis starting January 15, 2026, until the position is filled, so candidates are encouraged to apply as soon as possible.
Apply for the position here!
Senior Data Privacy Software Developer
Reporting to the Vicky Joseph Professor of Computer Science and Applied Mathematics at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), the focus of this position is to develop the OpenDP Library, a modular toolkit of differential privacy routines. You will work with privacy researchers to understand algorithms, implement the underlying architecture, and create and document public APIs. You will also help facilitate the growth of an open-source ecosystem.
The OpenDP Project is a flourishing community effort to build trustworthy, open-source software tools for statistical analysis of sensitive private data, providing the rigorous protections of differential privacy for individuals represented in the data. Upcoming projects include integrating OpenDP with differentially private methods for training AI models and supporting use cases in industry, as well as those that enable research in public health and medicine.
Job Specific Responsibilities:
- Collaborate with researchers on the design, planning, and implementation of software libraries for privacy-preserving data analysis and machine learning.
- Acquire a deep understanding of privacy algorithms through literature review and regular discussions.
- Apply firm understanding of data analysis use cases to develop flexible solutions to users’ needs.
- Build software to implement core privacy functionality, utility routines, and test suites.
- Develop and maintain support infrastructure for an open-source software library.
- Work in a team of developers and researchers in collaboration with outside experts.
- Provide regular communications to PIs and stakeholders with project updates.
- Write code design and development guides for future contributors.
- Create documentation for users with a wide range of backgrounds and levels of understanding.
- Present on DP and OpenDP to contributors and potential adopters.
- Abide by and follow the Harvard University IT technical standards, policies, and Code of Conduct.
Basic Qualifications:
- Minimum of five years’ post-secondary education or relevant work experience
Additional Qualifications and Skills:
- Fluency in Python, and either Rust (preferred) or other compiled language.
- Familiarity with machine learning frameworks, preferably including federated learning.
- Post-secondary degree(s) in Computer Science, Statistics, Data Science, or related fields.
- Exposure to differential privacy.