PhD Students and Postdoc Positions on Knowledge-Driven 6G Networks for Connected Mobility and Smart Manufacturing
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PhD Students and Postdoc Positions on Knowledge-Driven 6G Networks for Connected Mobility and Smart Manufacturing
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Universidad Miguel Hernández de ElchePhD Students and Postdoc Positions on Knowledge-Driven 6G Networks for Connected Mobility and Smart Manufacturing
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PhD Students and Postdoc Positions on Knowledge-Driven 6G Networks for Connected Mobility and Smart Manufacturing
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Universidad Miguel Hernández de ElcheGet AI-powered advice on this job and more exclusive features.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.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. Good English writing and speaking skills are required, as well as team working attitude, and self‐motivation.
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 done the PhD or have experience in one of the following research topics:
AI, design of wireless networks, V2X communications, autonomous driving. 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. Strong theoretical foundations and analytical modelling experience are also a plus. Critical thinking skills, team working attitude, and self-motivation are required. Proficiency in English writing and speaking is also required.
Benefits
Contract duration:
2 years for post-docs and 3 years for PhD students.
Starting date:
as soon as possible.
Interested candidates should send their application by email. The application is open until all positions are filled. Candidates should send their Curriculum Vitae and their Academic Certificate and transcript of records to Prof. Javier Gozalvez (j.Gozalvez umh es), Dr. Baldomero Coll-Perales (bcoll umh es) and Dr. Luca Lusvarghi (llusvarghi umh es). The subject of the email should be “Positions on Knowledge-Driven 6G Networks - Candidate name”. Applications will be continuously evaluated upon reception, and online interviews will be organized with the selected candidates until all positions are filled.
Seniority level
Seniority level Entry levelEmployment type
Employment type Full-timeJob function
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