Postdoktor (2 år) inom datasekretess och maskininlärning
Core
Developing privacy-aware machine learning models for complex and temporal data, focusing on differential/integral privacy and federated learning.
Role type
Postdoctoral researcher (Privacy-aware ML)
Builds
Privacy-preserving AI systems and algorithms
Domain
Data Science / Machine Learning / Privacy
Deliverable
production ML models
Required skills
Design of algorithms and methods for data protection and machine learning, Differential privacy, Integral privacy, Federated learning, Temporal data modeling, Synthetic data modeling
Preferred skills
Publications at top-tier conferences (NeurIPS, ICML, S&P, PETs, ESORICS)
Technologies
Federated learning frameworks, Privacy-preserving ML libraries
Responsibilities
Develop integrity-aware models for machine learning, Research privacy metrics and scenarios for centralized/decentralized data, Design algorithms for large-scale privacy-preserving ML
Seniority
Postdoctoral researcher
