We are searching for one or two new graduate students to join The Salon, who wish to study differentially private machine learning. Directions will focus on fundamental algorithmic methodology, working towards realizing differentially private machine learning in practice. The ideal candidate will be comfortable with understanding and developing new rigorous and mathematical arguments, while also enthusiastic about implementing, evaluating, and experimenting with these algorithms by writing code. Please browse the group’s past publications to assess the level of suitability – though a prospective student might not be completely familiar with the all arguments presented, they should have the maturity and motivation to learn them, and prepared to work towards producing work of this quality over the course of a year.
Applications are invited at both the Master’s (MMath Thesis) and PhD level. The deadline is December 15, 2020. Due to volume of requests, it may not be possible to respond to individual email inquiries, but please mention Le Salonneur’s name (Gautam Kamath) in your application. Applications are particularly encouraged from groups which are typically underrepresented in Computer Science, and all candidates will be evaluated holistically (i.e., their accomplishments based on the potentially varied opportunities they’ve been given).
Waivers for the GRE and application fee may be available on an individual basis, please contact email@example.com.
Depending on resources, there may be opportunities for a postdoctoral researcher. Please see instructions for applying on this page, and be sure to mention Gautam Kamath in your application.