Paolo Monti
1 month ago
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Postdoc in Mission-Critical Resilience for 6G Transport Networks Chalmers University of Technology in Sweden
Degree Level
Postdoc
Field of study
Computer Science
Funding
Available
Deadline
Aug 31, 2026
Country
Sweden
University
Chalmers University of Technology

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About this position
Chalmers University of Technology is recruiting a postdoc in Mission-Critical Resilience for 6G Transport Networks within the Division of Communications, Antennas and Optical Networks (CAOS) at the Department of Electrical Engineering in Gothenburg, Sweden.
The position is part of FiSRE (Towards Resilient 6G Networks), a Vinnova-funded Swedish-Finnish collaboration with academic and industry partners. The project aims to make resilience a built-in property of future 6G systems, alongside efficiency and sustainability, so that networks can continue delivering critical services under faults, cyber threats, physical damage, and extreme weather.
The successful applicant will work on the transport network layer connecting radio access, edge, and core. Research tasks include developing models, algorithms, and optimization methods for resilient 6G transport networks; estimating disruption risk; designing proactive reconfiguration and autonomous recovery mechanisms; and enabling self-healing and graceful degradation. Machine learning may be used where it adds value to the resilience framework.
You will be part of the group led by Professor Paolo Monti, whose research covers transport network design, resilience, and AI-driven automation for 5G/6G infrastructures. The work supports mission-critical scenarios and contributes to an end-to-end resilience proof of concept with Swedish and Finnish partners. The position also includes publication in leading journals and conferences, presentation of results at project meetings, and limited supervision of master’s and/or PhD students. There is also a possibility to teach at undergraduate or master’s level.
Applicants must hold a doctoral degree in Electrical Engineering, Computer Science, Communication Networks, or a related field by the employment decision date. Strong background in communication and transport network design, network resilience or survivability, network optimization, programming skills such as Python, mathematical optimization, network modelling, machine learning for networking, and strong English communication skills are required. Teaching familiarity and potential in research and education are also expected.
The appointment is a temporary full-time postdoc for two years with a possible one-year extension. Physical presence is required throughout the appointment, and a valid residence permit must be available by the start date. Applications are reviewed continuously, and the deadline is 2026-08-31.
To apply, prepare a comprehensive CV, publication list, teaching/pedagogical experience, and a tailored personal letter describing your planned contribution to the FiSRE project and how your background fits the resilience and transport-network focus. Applications must be submitted online; email applications and incomplete submissions will not be considered.
Funding details
Available
What's required
A doctoral degree in Electrical Engineering, Computer Science, Communication Networks, or a related field, or an equivalent foreign degree, must be completed no later than the employment decision date. Applicants should have a strong background in communication and transport network design, with demonstrated expertise in network resilience or survivability and network optimization. Solid programming skills, for example in Python, and hands-on experience with mathematical optimization and network modelling are required. A good working understanding of machine learning and its application to networking problems is expected. Strong written and verbal communication skills in English are required. The candidate is expected to be somewhat accustomed to teaching and to show good potential in research and education. Meritorious qualifications include having obtained the doctoral degree within the last three years, experience with protection/restoration and risk-aware optimization for transport networks, exposure to 5G or 6G transport, Xhaul, network slicing, SDN, or software-based network control, familiarity with modelling and simulation tools and resilience/reliability metrics, machine learning approaches such as reinforcement learning, graph neural networks, or uncertainty quantification, publications in leading networking or communications venues, and interest in mission-critical or critical infrastructure scenarios.
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