PhD Candidate: Secure Computation Technologies and Applications to Machine Learning
LIACS, Leiden University
Secure Computation Technologies, such as Multiparty Computation, allow the purposeful processing of private data (distilling value from such data), without compromising the privacy of this data. Today’s interconnected world, smart applications, and global business, necessitating the use of collaborative analytics, require the collection and processing of private information. In this PhD trajectory you will be exploring ways and developing protocols and primitives that enhance the security, functionality, and efficiency of secure computation technologies (e.g., multiparty computation – MPC), when designed for particular application scenarios, such as private machine learning use-cases.
Conduct original and novel research in the field of Secure Computation Technologies;
Design novel protocols for privacy-preserving (machine learning) applications;
Publish and present scientific articles at international journals and conferences;
Engage in collaborations in academia and industry;
Assist in relevant teaching activities.
Contact: Eleftheria Makri
In this 4-year PhD trajectory, you are expected to:
The position is fully funded for 4 years.
Last updated: 2025-06-18 posted on 2025-06-16