Open Positions in the Privacy Tools for Sharing Research Data Project
The Privacy Tools project regularly seeks students, interns, postdocs, and visitors 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. Below are some of the positions available, with instructions on how to apply. For general information, email email@example.com or one of the PIs.
The Privacy Tools project develops ways for scientists to share research data for producing replicable, open science, without compromising the privacy of the individual research subjects whose data is used. Past students wrote or contributed to publishable to publishable research papers in this fast-moving field, and we expect the same in future years. The work across the different projects includes elements such as:
- Theory: proving mathematical theorems about what is achievable in the framework of “differential privacy,” which is a very active area of research in theoretical computer science and other fields.
- Experimental algorithms: implementing, optimizing, and testing algorithms that perform useful data analysis tasks and satisfy “differential privacy” or other privacy metrics.
- Empirical research: surveying social science datasets and analysis methods to determine the fit with different privacy technologies.
- Software development: including 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: collaborating 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
- 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