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:jnear@uvm.edu,david.darais@uvm.edu) 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