Researcher on Embodied and Physical AI for Networked Intelligent Systems (m/f/x)

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

Researcher on Embodied and Physical AI for Networked Intelligent Systems (m/f/x)

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 looking for a highly motivated researcher to join an ambitious research program aimed at developing the next generation of embodied and physical artificial intelligence systems. The position addresses the fundamental challenge of how intelligent physical agents - including robots, autonomous machines, mobile manipulators, drones, and intelligent production systems - can perceive, reason, learn, communicate, and act through continuous interaction with the physical world.

Particular emphasis will be placed on embodied intelligence, active inference, networks of physical AI agents, and their integration into adaptive and autonomous networked intelligent systems (e.g., factories of the future).

The researcher will join the Institute of Networked Energy-Efficient Systems at the Faculty of Electrical Engineering and Information Technology, Ruhr University Bochum. This is a full-time position with immediate availability.

Scope: full-time Duration: fixed-term, 3 years Start: at the earliest possible date Apply by: 2026-10-05

Your tasks

• Design and develop novel architectures for embodied and physical AI systems operating across heterogeneous robotic platforms, intelligent machines, communication networks, and edge-cloud infrastructures.
• Investigate embodied intelligence, multimodal perception, world modelling, sensorimotor learning, and closed-loop interaction between intelligent agents and their physical environments.
• Develop active inference and probabilistic reasoning approaches for perception, prediction, planning, control, and autonomous decision making under uncertainty.
• Design communication, coordination, and information-sharing mechanisms for networks of physical AI agents operating under bandwidth, latency, reliability, and energy constraints.
• Explore learning-based approaches for autonomous adaptation, multi-agent coordination, continual learning, reinforcement learning, imitation learning, and foundation models for physical agents.
• Develop digital twin and simulation frameworks connecting virtual environments, physical AI agents, production systems, and real-world factory processes.
• Prototype and experimentally validate proposed solutions using robotic simulation platforms, edge-cloud infrastructures, industrial automation environments, and real robotic systems.
• Collaborate closely with researchers working on embodied AI, robotics, artificial intelligence, distributed systems, cloud-edge computing, communication networks, industrial automation, and autonomous systems.
• Participate in interdisciplinary research projects involving both academic and industrial partners.
• Publish research findings in leading conferences and journals in embodied AI, robotics, AI, networking, distributed systems, autonomous systems, and intelligent manufacturing.
• Contribute to research project planning, execution, reporting, and proposal preparation.
• Assist in the supervision of student projects and junior researchers.
• Support teaching activities in areas related to artificial intelligence, embodied intelligence, robotics, cloud-edge systems, distributed computing, and future communication systems.
• Support the organization of outreach activities related to the Institute’s research activities.

Your profile

• Master’s degree in Electrical Engineering, Computer Science, Telecommunications, or a related field.
• Prior publications in renowned transactions, journals, and the proceedings of reputable conferences are highly desirable and advantageous.
• Embodied AI, Physical AI, Robotics, and Autonomous Systems, Artificial Intelligence, Machine Learning, and Deep Learning
• Multi-Agent Systems and Networks of Physical AI Agents, Reinforcement Learning, Imitation Learning, and Active Inference
• Distributed Systems, Cloud-Edge Computing, and Networked Intelligence, Robot Operating System (ROS2) and robotic software architectures
• Computer Vision, Multimodal Perception, and Sensor Fusion
• World Models, Semantic Reasoning, Probabilistic Inference, and Knowledge Representation, Optimization, Planning, Control, and Decision-Making Algorithms
• Familiarity with frameworks such as Isaac Sim, Gazebo, PyTorch, ROS2, Kubernetes, Docker, and related AI/robotics platforms
• Knowledge of industrial automation, cyber-physical production systems, digital twins, 5G/6G communication technologies, or factory-of-the-future concepts is highly desirable.
• Ability to independently and proactively design, execute, and analyse experimental research.
• Excellent analytical and problem-solving skills , Strong scientific writing and communication abilities
• Ability to collaborate effectively in multidisciplinary and international teams , Strong motivation to pursue high-impact research

[https://jobs.ruhr-uni-bochum.de/jobposting/210883376a416eede7fd37ad8780881cfb52dc3d0?ref=AfA](https://jobs.ruhr-uni-bochum.de/jobposting/210883376a416eede7fd37ad8780881cfb52dc3d0?ref=AfA)