.The UWICORE laboratory at the Universidad Miguel Hernández (UMH) de Elche (Spain) offers several PhD student & post-doc positions on Knowledge-Driven 6G Networks for Connected Mobility and Smart Manufacturing.TasksFuture smart networks, including 6G, should go beyond pure communication systems and integrate sustainably computing, sensing, intelligence and connectivity capabilities for a proactive and knowledge-driven management of communications and networks solutions that will scalably and reliably support deterministic service levels and control processes. This should include hybrid intelligence solutions with reasoning capabilities to shift the focus of communications from the reliable and timely delivery of data to the semantic and goal-oriented transmission of data that is relevant and valuable. In this context, our lab is offering several research positions on the following topics:Design of novel Artificial Intelligence (AI)-based solutions (including generative AI) to process and interpret contextual information for generating collective awareness, predict the evolution of context, and determine the relevance and semantic value of information for optimizing the efficiency and scalability of 6G communications and networks.Causal reasoning mechanims to facilitate explainability, improve accuracy and reduce computational cost of AI-based knowledge generation for the design of 6G communications and networks.Study the role of infrastructure (with additional sensing capabilities) for collaboratively improving the knowlegde generation with devices and sensors.Design of knowledge-driven, AI-based, and semantic and goal-oriented 6G networking protocols for improving the scalability of networks and the capacity to sustain deterministic service levels. The research will focus on the opportunities, challenges and priorities of Connected and Automated Mobility (CAM, including V2X networks) and smart manufacturing, two verticals in which the lab has significant expertise. Both verticals embed expanding connectivity, processing, sensing, autonomy, control, and AI capabilities that empower a more cognitive and cost-effective management of future networks.RequirementsPhD candidates should have a Master in Computer Science or Engineering, Telecoms, or Electrical Engineering (or closely related disciplines). Interest or experience in one of the following topics is required: 5G and beyond wireless networks, Artificial Intelligence (Deep Learning, Reinforcement Learning), V2X communications, autonomous systems (e.G. connected and automated vehicles, and smart robots in manufacturing). The candidate should have good programming skills (e.G. C++, Python) as well as good theoretical foundations, analytical modelling and critical thinking skills. Publications in journals and conferences are positively considered but not required. Experience with machine learning software (PyTorch, Keras, or TensorFlow) is a plus