The Privacy Tools Project seeks students, interns, postdocs, and visiting researchers in Computer Science, Statistics, Government, Mathematics, Law, and Social Sciences with Quantitative Experience, particularly those with an interest in learning about or working on Data Privacy.
The dates of the Summer 2024 program are June 3rd - August 9th. It is preferred that students join full time and in person for the full 10-week program, but there are also options for part-time, remote, and/or term-time work. There are a limited number of paid internship positions, so students who can apply for their own summer research funding are encouraged to do so and indicate it in their application.
Available positions are listed below, with instructions on how to apply. For general information, email privacytools-info@seas.harvard.edu or one of the PIs. Applicants will also be considered for positions in the OpenDP Project, which is an outgrowth of the Privacy Tools Project."
The Privacy Tools Project develops ways for scientists to share research data for producing open, replicable science without compromising the privacy of the individual research subjects whose data is used. Past students have written and contributed to publishable research papers in this fast-moving field, and we expect the same in future years. Work across the different projects includes:
- Theory: prove mathematical theorems about what is achievable in the framework of differential privacy.
- Experimental algorithms: implement, optimize, and test algorithms that perform useful data analysis tasks and satisfy differential privacy and other privacy metrics.
- Empirical research: survey social science datasets and analysis methods to determine the fit with different privacy technologies.
- Software development: develop software for statistics, user interfaces, and data visualization.
- Programming languages and computer security: design and implement programming language tools to ensure differential privacy and combine it with other computer security models.
- Law: develop legal instruments and policy recommendations that complement new privacy-preserving technologies.
- Interdisciplinary interaction: collaborate with computer scientists, social scientists, lawyers, and statisticians.
Useful background includes any of the following:
- Theoretical computer science, especially algorithms
- Data science, e.g. statistics and/or machine learning
- Programming (in R, Java, Scala, Python, Javascript, or D3)
- Quantitative analysis of social science data, especially regression ("least squares", or OLS)
- User interfaces and user experience testing
- Programming language design and implementation
- Law, especially privacy law
Applicants will also be considered for positions at OpenDP.