Post-doctorant en apprentissage décentralisé sûr, conficentiel et explicable

About the role

Télécom SudParis is seeking a post-doctoral researcher to work on secure, confidential, and explainable decentralized machine learning. The role involves analyzing security and privacy challenges in AI deployment, developing privacy-preserving machine learning methods, and exploring the trade-offs between robustness, privacy, and explainability in federated learning environments.

Responsibilities

• Analyze security, privacy, and ethical issues related to AI deployment in critical domains.
• Design and evaluate privacy-preserving approaches for decentralized learning environments.
• Identify and characterize security vulnerabilities in collaborative and federated learning.
• Study explainable AI (XAI) methods to improve transparency and interpretability of AI models.
• Develop and experiment with methods to reconcile transparency and privacy protection.
• Contribute to the dissemination of research results through scientific publications and conference presentations.

Required skills

• Artificial Intelligence
• Machine Learning
• Cybersecurity
• Federated Learning
• Advanced Mathematics
• English

Nice to have

• Homomorphic encryption
• CKKS
• Differential Privacy
• Explainable AI
• XAI
• Privacy-Enhancing Technologies
• PET

Qualifications

• Doctorat or PhD in Computer Science obtained within the last 3 years

Benefits

• 44 days of leave
• On-site restaurant and cafeteria
• Public transport subsidy
• Staff association
• Sports association

About the Company

Télécom SudParis is a public engineering school recognized for its scientific excellence in digital sciences and technologies. It is part of the Institut Mines-Télécom, the leading group of engineering schools in France, and a co-founder of the Institut Polytechnique de Paris.