Do you want to build 6G networks that keep working when everything else fails? Join the Division of Communications, Antennas and Optical Networks at the Electrical Engineering Department at Chalmers to develop mission-critical resilience for the transport networks that will carry 6G.
About us
At the Department of Electrical Engineering, research and education are performed in the areas of Communications, Antennas and Optical Networks, Systems and Control, Signal Processing and Biomedical Engineering, and Electric Power Engineering. We work with sustainable and smart solutions to societal challenges, such as energy efficiency and electrification in areas ranging from transport and production systems to communication solutions and biomedical engineering.
The Division of Communications, Antennas, and Optical Networks (CAOS) conducts research and education in wireless and optical technologies for communication and sensing. Combining fundamental and applied research, we address challenges in sustainability, security, and next-generation communication systems. The division also plays a key role in engineering education, particularly within the Master's programme in Information and Communication Technology.
You will work in the group led by Professor Paolo Monti, whose research focuses on transport network design, resilience, and AI-driven network automation for 5G and 6G infrastructures.
About the research project
This position is part of FiSRE (Towards Resilient 6G Networks, a Swedish and Finnish Joint Undertaking), a Vinnova-funded collaboration between leading Swedish and Finnish universities and industry partners. FiSRE aims to make resilience a built-in design property of 6G, alongside efficiency and sustainability, so that networks continue to deliver critical services not only during faults but also under hostile or degraded conditions, such as cyber threats, physical infrastructure damage, and extreme weather.
Your work focuses on the transport network layer that interconnects radio access, edge, and core. You will design and optimize resilience mechanisms that estimate disruption risk and proactively reconfigure the transport network to enable autonomous recovery, self-healing, and graceful degradation, drawing on machine learning where it strengthens these methods. The research supports mission-critical scenarios and feeds into an end-to-end resilience proof of concept developed together with Swedish and Finnish partners.
Who we are looking for
The following requirements are mandatory:
- A doctoral degree in Electrical Engineering, Computer Science, Communication Networks, or a related field, or an equivalent foreign degree. This eligibility requirement must be met no later than the time the employment decision is made.
- A strong background in communication and transport network design, with demonstrated expertise in network resilience or survivability and in network optimization.
- Solid programming skills (for example in Python) and hands on experience with mathematical optimization and network modelling.
- A good working understanding of machine learning and its application to networking problems.
- Strong written and verbal communication skills in English.
You are expected to be somewhat accustomed to teaching and to demonstrate good potential within research and education.
The following experience will strengthen your application:
- It is highly meritorious if the doctoral degree has been obtained within the last three years prior to the application deadline.
- Experience with resilience or survivability techniques for transport networks, including protection, restoration, and risk-aware optimization.
- Experience with 5G or 6G transport, Xhaul, network slicing, SDN, or software-based network control.
- Familiarity with network modeling and simulation tools and with resilience and reliability metrics.
- Experience applying machine learning to networking problems, for example, reinforcement learning, graph neural networks, or uncertainty quantification.
- A track record of publications in leading networking or communications venues.
- Interest in mission-critical and critical infrastructure scenarios.
What you will do
- Develop models, algorithms and optimization methods for resilient 6G transport networks, using machine learning where it adds value.
- Design mechanisms for disruption risk estimation, proactive reconfiguration, self healing and graceful degradation at the transport layer.
- Contribute to the FiSRE end to end resilience proof of concept together with Swedish and Finnish academic and industry partners.
- Publish in leading international journals and conferences and present results at project meetings.
- Supervise master’s and/or PhD students to a certain extent
- Possibility to engage in teaching at undergraduate/master’s level
The position is meritorious for future roles in academia, industry, or the public sector.
Contract terms
The position is a temporary full-time employment for two years with the possibility of a one-year extension.
The position requires physical presence throughout the entire employment. A valid residence permit must be presented by the start date, otherwise the offer may be withdrawn.
What we offer
- As a postdoc at Chalmers, you are an employee and enjoy all employee benefits. Read more about working at Chalmers and our benefits for employees.
- A dynamic and inspiring working environment in the coastal city of Gothenburg.
- Read more about Sweden’s generous parental leave, subsidized day care, free schools, healthcare etc at Move To Gothenburg.
Chalmers is dedicated to improving gender balance and actively works with equality projects, such as the GENIE Initiative for gender equality and excellence.
If Swedish is not your native language, Chalmers offers Swedish courses to help you settle in.
Application procedure
The application should be written in English be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system does not support Zip files.
CV
- A comprehensive CV, including a complete list of publications.
- Details of previous teaching and pedagogical experience.
Personal letter
- A brief introduction about yourself.
- A description of how concretely you would contribute to this specific project: which research questions you would tackle, the approach you would take, and how your background fits the resilience and transport network focus of FiSRE. Letters that remain generic will be considered less competitive.
- A summary of your previous research fields and key research outcomes, and an outline of your future goals and research focus.
- An outline of your future goals and research focus.
Use the button at the foot of the page to reach the application form.
A background check may be conducted as part of the application process.
Please note: The applicant is responsible for ensuring that the application is complete. Incomplete applications and applications sent by email will not be considered. Contact details to references will be requested after the interview.
We welcome your application no later than August 31, 2026.
Applications are reviewed continuously as they arrive, so we encourage you to apply early.
For questions, please contact:
Paolo Monti
Professor in Communication Networks
[email protected] - +46 31 772 60 27
Carlos Natalino
Researcher
[email protected] - +46 31 772 60 26
*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***
Chalmers University of Technology in Gothenburg conducts research and education in technology and natural sciences at a high international level. The university has 3100 employees and 10,000 students, and offers education in engineering, science, shipping and architecture. With scientific excellence as a basis, Chalmers promotes knowledge and technical solutions for a sustainable world. Through global commitment and entrepreneurship, we foster an innovative spirit, in close collaboration with wider society.
Chalmers was founded in 1829 and has the same motto today as it did then: Avancez – forward.
