Post-Doctoral Research Visit F/M Distributed Learning for Streaming Data

Highlights

• Design private real-time distributed learning for streaming edge data.
• Explore data freshness and personalization in federated learning systems.
• Co-design communication and learning for fresh streaming sensor data.

What they offer

• Subsidized meals
• Partial reimbursement of public transport costs
• 7 weeks annual leave plus 10 RTT days
• Professional equipment and access to vocational training
• Social security coverage

Ideal candidate

Curious, collaborative researcher fresh from a PhD who loves blending rigorous theory with real experiments and tackling real-time data challenges with international partners.

Requirements

• PhD defended no later than December 31, 2026
• PhD in theoretical or experimental aspects of distributed or federated learning, time-series learning, differential privacy or communication networks for learning