PhD Students and Postdoc Positions on Knowledge-Driven 6G Networks for Connected Mobility and Smart Manufacturing

hace 17 horas


Elche, Alicante, España Universidad Miguel Hernández De Elche-Uwicore A tiempo completo
Research Opportunities in 6G Networks for Connected and Automated Mobility and Smart Manufacturing

The UWICORE laboratory at the Universidad Miguel Hernández (UMH) de Elche (Spain) is offering several PhD student & post-doc positions on Knowledge-Driven 6G Networks for Connected Mobility and Smart Manufacturing.

This 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.

The research will involve the design of novel Artificial Intelligence (AI)-based solutions 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 mechanisms will be used to facilitate explainability, improve accuracy and reduce computational cost of AI-based knowledge generation for the design of 6G communications and networks.

The role of infrastructure (with additional sensing capabilities) will be studied for collaboratively improving the knowledge generation with devices and sensors.

Knowledge-driven, AI-based, and semantic and goal-oriented 6G networking protocols will be designed for improving the scalability of networks and the capacity to sustain deterministic service levels.

Requirements PhD 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.



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