The UVM Programming LAnguages, Information-security and Data-privacy (PLAID) Lab is seeking one MS or PhD student to work on the Duet project—advised by [Joe Near] and [David Darais]—for the spring 2019 semseter. The position is a fully funded Graduate Research Assistantship (GRA), with an option to continue through the summer and fall 2019 semesters. [Joe Near]: http://www.uvm.edu/~jnear/ [David Darais]: http://david.darais.com Duet is a programming language for data privacy applications developed by Joe Near and David Darais along with collaborators at UVM, UC Berkeley and Cornell. Duet approaches data privacy by bounding the information that is learned about private data during some data analysis, such as querying a database or training a machine learning model. Duet uses *differential privacy* to ensure that analysis results do not violate an individual's privacy, and employs a novel *type system* to statically guarantee that this quantity is negligibly small when performed on private data. The design of Duet, its applications, and an evaluation of its effectiveness is currently in submission for publication. [[Duet Paper]] [Duet Paper]: /assets/papers/duet/duet.pdf We are seeking applicants who have some background in at least one of the following topics: differential privacy, databases, machine learning, programming language semantics, compilers, type systems, program analysis or software verification. To apply for the position send email addressed to both [Joe Near and David Darais](mailto:firstname.lastname@example.org,email@example.com) indicating your interest, along with your resume and a short paragraph (2–3 sentences) describing your background in any of the above topics. Please respond by Thursday, Dec 13.
Last updated Dec 5, 2018