Researcher in Distributed Intelligence and Cloud-Edge Learning | Researcher (m/f/x) in Distributed Intelligence and Learning Across the Cloud-Edge Continuum

Ruhr-Universität Bochum

Bochum, Nordrhein-Westfalen, Deutschland
Published Feb 10, 2026
Full-time
Fixed-term

Job Summary

This full-time research position at Ruhr University Bochum focuses on the intersection of AI and network systems. As a researcher, you will design and evaluate distributed learning algorithms, exploring model splitting and collaborative inference across heterogeneous nodes. Your day-to-day work involves prototyping solutions on edge-cloud platforms, investigating privacy-preserving mechanisms, and co-designing AI models with network architectures. Beyond core research, you will collaborate with cross-functional teams of engineers, publish findings in top-tier journals, assist in grant proposal writing, and support teaching activities within the Faculty of Electrical Engineering and Information Technology. This role is particularly attractive for those seeking to pioneer energy-efficient cloud networks in a highly dynamic, international academic environment. The position offers a three-year fixed-term contract with the opportunity to influence the future of 5G/6G and edge computing infrastructures.

Required Skills

Education

Above-average Master’s degree in Machine Learning, Computer Science, or a related field.

Experience

  • Professional experience in machine learning and AI methodologies
  • Experience in distributed or federated learning environments
  • Experience in designing and executing experimental research independently
  • Desirable: Initial experience publishing in renowned journals or conference proceedings
  • Desirable: Experience with real-time systems and edge computing
  • Desirable: Experience in AI-driven network management and orchestration

Languages

English (Fluent)

Additional

  • The position is a fixed-term contract for 3 years. Candidates must be able to support teaching activities and assist in the organization of academic workshops and conferences.