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Researcher (m/f/x) on Autonomous Cloud-Edge Continuum Orchestration

The Institute of Networked Energy-Efficient Systems is dedicated to advancing autonomous, energy-efficient cloud-based networks that support cutting-edge services and innovations. We are assembling a talented international team committed to pioneering research and teaching in this dynamic field.

We are seeking a highly motivated researcher (m/f/x) to work on next-generation autonomous orchestration mechanisms across the cloud-edge-device continuum. The position addresses fundamental research challenges in the management of distributed compute, storage, and networking resources under mobility, uncertainty, and competing multi-objective constraints. The successful candidate will develop AI-native orchestration frameworks that move decisively beyond static placement strategies and rule-based lifecycle management, enabling self-optimizing and self-evolving systems capable of continuous adaptation across heterogeneous cloud and edge environments. The researcher (m/f/x) will join the Institute of Networked Energy-Efficient Systems at the Faculty of Electrical Engineering and Information Technology, Ruhr University Bochum.

Scope: full-time
Duration: fixed-term, 3 years
Start: at the earliest possible date
Apply by: 2026-03-23

Your tasks:

· Research and Development:

o Design novel orchestration architectures and algorithms for dynamic service placement, migration, and scaling across the cloud-edge continuum.

o Devise and evaluate learning-based methods and control-theoretic approaches to balance latency, reliability, energy efficiency, cost, and sustainability objectives in real time.

o Prototype and experimentally validate the proposed solutions on real-world platforms, including Kubernetes-based edge clusters and private 5G/6G infrastructures

· Collaboration: Work collaboratively with cross-functional teams, including hardware engineers (m/f/x), software developers (m/f/x), and other researchers (m/f/x) to integrate AI solutions with network and cloud infrastructure.

· Publication and Presentation: Publish research findings in high-impact journals and present at international conferences and symposiums to disseminate knowledge and advance the field.

· Project Management: Assist in the management of research projects, including the preparation of reports, grant proposals, and progress updates.

· Teaching Assistance: Help with teaching courses related to clouds and networks, contributing to curriculum development and providing support to students (m/f/x).

· Event Organization: Support the organization of online webinars, events, workshops, and conferences related to the Chair's activities.

Your profile:

· Education:

o above-average Master’s degree in Electrical Engineering, Computer Science, Telecommunications, or a related field.

o initial experience in publications in renowned transactions, journals, and the proceedings of reputable conferences are desirable and advantageous.

· Technical Skills:

o Solid experience with Kubernetes. Experience with ClusterAPI is advantageous.

o Good analytical skills and relevant experience in any of the following: network switching and routing, software-defined networking, mathematical optimization, and machine learning.

o Proficiency in theory and technologies in AI, distributed intelligence, including deep learning, reinforcement learning, meta-learning, transfer learning, offline reinforcement learning, and diffusion model.

o Expertise in programming languages (Python, C/C++, Java), AI/ML frameworks (e.g., PyTorch, JAX), network simulators (e.g., ns-3, OMNeT++), and hardware development (e.g., FPGA, embedded systems).

o Knowledge of 5G and beyond communication standards and technologies is highly desirable.

o Ability to independently design, execute, and analyse experimental research.

· Soft Skills:

o Excellent problem-solving skills and analytical thinking.

o Strong written and verbal communication skills in English.

o Ability to work both independently and as part of a multidisciplinary team.

· Preferred Qualifications:

o Experience in edge intelligence, meta-learning, transfer learning.

o Familiarity with AI-driven network management and orchestration.

o Experience in EdgeAI training, deployment, and demo.

o Knowledge of security and privacy issues in wireless communications.

https://jobs.ruhr-uni-bochum.de/jobposting/c5cb3ea721c7d4510181b875a7061e84b00f8e170?ref=AfA