Summer internship positions in the PROBIC group

1. Differentially private machine learning (multiple positions)

Background: machine learning, mathematics, programming skills

Differentially private machine learning studies learning methods that can operate while guaranteeing privacy of the data subjects. These methods can be applied to solving predictive learning problems on private data but also for creating provably anonymised data sets. We apply differential privacy in the context of various modern machine learning methods, including Bayesian methods and deep learning.

In this project you will participate in developing and applying new differentially private machine learning methods. Depending on your background and interests, the work will combine working on the mathematical theory of differential privacy, general methods development, implementation and application of the developed methods in different applications.