Elx / Elche, Valencian Community, Spain · On-site
<p>The Networked Systems Lab of the Universidad Miguel Hernández (UMH) de Elche (Spain) offers several fully-funded PhD positions in Networked Physical AI Multi-Agent Systems.</p> <p>Successful candidates will work in an…
Skills: Artificial Intelligence, Physical AI, Multi-agent systems, 6G networks, Mobile robotics
Elx / Elche, Valencian Community, Spain • On-site
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Successful candidates will conduct research at the intersection of Physical AI, multi-agent systems, and 6G networks to develop solutions for autonomous agents in dynamic environments. They will also contribute to active projects, publish in top-tier journals, and collaborate with international academic and industrial partners.
Candidates must hold or be close to completing a Master’s degree in Robotics, Computer Science, Electrical, Electronic, or Telecommunications Engineering. Strong programming skills in C++ or Python and a solid theoretical foundation in AI or autonomous systems are required.
The Networked Systems Lab of the Universidad Miguel Hernández (UMH) de Elche (Spain) offers several fully-funded PhD positions in Networked Physical AI Multi-Agent Systems.
Successful candidates will work in an internationally recognized research group with extensive collaborations in academia and industry, publish in top-tier journals and conferences, contribute to active projects (and proposals) and have opportunities for international collaborations. The Networked Systems Lab (formerly UWICORE laboratory) is internationally-recognized for its research on wireless networking for connected and automated mobility and smart manufacturing. The laboratory is actively involved in EU and national projects, standardization and R&D contracts with industrial partners. Some of the PhD projects will be carried out in collaboration with industrial partners in the US. The laboratory is located in the Mediterranean coast of Spain (Elche) and is part of the Department of Communications Engineering of the Universidad Miguel Hernández (UMH) and of the Institute for Engineering Research (I3E) of Elche.
Future Physical AI systems will be characterized by large populations of autonomous embodied agents – including collaborative robots and connected autonomous vehicles– operating in shared physical environments. Unlike today's agentic AI systems, which primarily execute predefined workflows in structured and well-defined digital environments, future Physical AI agents will have to perceive, reason and act under unstructured and continuously evolving real-world conditions and objectives. This calls for a fundamental rethinking of how agents interact, requiring intelligence and semantic and task-oriented networking to be co-designed so that agents can collaboratively construct meaningful representations of the physical world, reason over existing (shared) context and knowledge, and adapt their networking and interactions to efficiently accomplish individual and collective tasks.
Our lab is offering several PhD positions on research at the intersection of Physical AI, multi-agent systems, and 6G networks. The research will focus on developing solutions that enable autonomous agents to perceive, reason, network, and collaborate effectively in dynamic real-world environments. The research may also include interactions between embodied agents and agents at the 6G edge-cloud continuum infrastructure, as well as AI-network-control co-design. Research will initially be framed in collaborative mobile robotics and connected automated mobility, while developing scientific foundations that generalize to a broader range of cyber-physical systems. Specific research topics will be discussed during the interviews, and they can be co-defined with selected candidates based on their background, expertise, and research interests. The positions are for three years and will start as soon as possible. The positions are fully funded according to the Spanish PhD employment scheme and include full social security benefits.
Candidates should hold (or be close to completing) a Master’s degree in Robotics, Computer Science, Electrical, Electronic, or Telecommunications Engineering (or related disciplines). Strong interest or experience in one or more of the following topics is required: Artificial Intelligence, Physical AI, autonomous systems (e.g., mobile robotics and connected and automated vehicles), multi-agent systems, networking, 6G. Candidates should have good programming skills (e.g., C++ and/or Python) as well as good theoretical foundations and strong critical thinking skills. Experience with popular machine learning frameworks (e.g., PyTorch, TensorFlow) or simulation environments is considered a plus, but not required. Previous research experience or publications are positively considered but are not required. Good English writing and speaking skills as well as curiosity, self-motivation, and team-working attitude are essential.