Faculty of Electrical Engineering and Information Technology :
Chair of Networked Energy-Efficient Systems
In order to fill a fixed-term position in full-time (39.83 hours/week = 100%) at the earliest possible date, we are looking for a
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 |
· 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.
· 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.
The position is salaried and based on the collective agreement of the Länder (TV-L). If the personal and collective agreement requirements are met, the employee will receive pay grade E13 TV-L.
Further information can be found at https://oeffentlicher-dienst.info/ (in German).
The place of work is Ruhr University Bochum.
RUB sees itself as a university with an international presence. The campus languages are German and English. Competence in at least one of the two languages and the willingness to learn the other are a prerequisite. RUB provides corresponding free courses for employees.
German language courses are offered by the University Language Center (ZFA) in the field of German as a Foreign Language (DaF).
https://www.daf.ruhr-uni-bochum.de/sbgk/index.html.en
The Staff Council has the right to participate in all selection interviews. At the request of a candidate (m/f/x), it will ensure its participation in the entire procedure. Please contact wpr@rub.de.
The Ruhr-Universität Bochum is one of Germany’s leading research universities, addressing the whole range of academic disciplines. A highly dynamic setting enables researchers and students to work across the traditional boundaries of academic subjects and faculties. To create knowledge networks within and beyond the university is Ruhr-Universität Bochum’s declared aim.
The Ruhr-Universität Bochum stands for diversity and equal opportunities. For this reason, we favour a working environment composed of heterogeneous teams, and seek to promote the careers of individuals who are underrepresented in our respective professional areas. The Ruhr-Universität Bochum expressly requests job applications from women. In areas in which they are underrepresented they will be given preference in the case of equivalent qualifications with male candidates. Applications from individuals with disabilities are most welcome.
Prof. Dr. Tarik Taleb
, Tel.: +49 234 32 15140
Tom Schockenhoff
, Tel.: +49 234 32 15140
Travel costs, accommodation costs and loss of earnings or other application costs for job interviews can unfortunately not be reimbursed.
We look forward to receiving your application via our online application portal by 2026-03-23. Please make sure to mention the reference number ANR 5357.