The UWICORE laboratory at the Universidad Miguel Hernández (UMH) de Elche (Spain) offers several post-doc and PhD student positions on 6G Vehicle-to-Everything (V2X) Communications. Research will focus on solutions for designing scalable 6G V2X networks for Connected, Cooperative and Automated Mobility (CAM), with a focus on novel semantic V2X communications, AI-based collective awareness and networking, and V2N (vehicle to network)-based solutions. The research will design novel solutions for a paradigm shift in V2X communications where, rather than focusing on ensuring the reliable and timely transmission of data, we focus on selecting and transmitting the relevant information to scalably convey the desired message for the intended receivers and the target applications. The relevance of the information becomes the focus of the communications process, and such relevance is highly dependent on an accurate knowledge of the context of the communications process. To this aim, the rich communications and sensing V2X ecosystem where vehicles and infrastructure/network collaborate represent an opportunity to develop scalable 6G V2X networks.
Tasks The candidates will contribute to one or several of the following research activities in the context of 6G V2X:
Design of novel Artificial Intelligence (AI)-based solutions to process contextual information, generate collective awareness, and determine the relevance and semantic value of information. Design of semantic and goal-oriented V2X communication protocols for scalable 6G V2X networks, including novel semantic Key Performance Indicators (KPIs) and scalable implicit feedback mechanisms. Design of Vehicle-to-Network-to-Everything (V2N2X) solutions for deterministic support of CAM services in an interoperable multi-stakeholder framework with data sharing in the IoT-edge-cloud continuum. Development of an advanced CAM simulation platform that integrates a realistic 3D modelling of the driving environment (CARLA) with a realistic autonomous driving software stack (AUTOWARE) and V2X connectivity. Requirements Post-doc candidates should have a PhD in Computer, Telecoms, Electrical or Robotics Engineering (or closely related fields), and a high-quality track record of publications in relevant journals and conferences. Preferably, the candidate should have experience in one of the following research topics: Artificial Intelligence (Deep Learning, Reinforcement Learning), V2X communications, autonomous driving, and autonomous robotics. Experience with discrete-event simulators, Robot Operating System (ROS), autonomous driving simulators (CARLA) and software (Autoware), and the design of AI-based solutions will be positively considered. Proficiency in programming languages such as C++ and Python, and experience with software development, debugging, and deployment is required. Experience with machine learning software such as PyTorch, Keras, or TensorFlow is a plus.
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