Ph.D. student in Intelligent and Reliable Management of Next Generation Networks

The University of Applied Sciences and Arts of Southern Switzerland (SUPSI) has opened a full time (100%) position for a PhD student in Trustworthy Data-driven Automated Network and Service Management for Next Generation Networks at the Department of Innovative Technologies (DTI) located in Lugano, within the Institute of Information Systems and Networking (ISIN). The contract starts 1st January 2026 or date to be agreed upon.

Scope and purpose of the position

The Eureka Cluster CELTIC-NEXT project SUSTAINET-Advance aims to enhance the sustainability, resilience, and security of future 5G/B5G/6G networks by leveraging advanced technologies such as neuromorphic computing and optical networking. A particular focus is placed on the interdependence between energy and communication networks, fostering a more climate-resilient and technologically sovereign Europe. The project integrates research in frictionless network performance, scalable connectivity, and secure-by-design AI to support the seamless, intelligent automation of next-generation communication infrastructures.

As machine learning (ML) and artificial intelligence (AI) techniques become increasingly central to automated network control and orchestration, ensuring the trustworthiness of these AI-based solutions is a critical challenge. Trustworthy AI is essential for enabling reliable, secure, explainable, and efficient network operations across a broad set of use cases, ultimately contributing to building sustainable and trustworthy network infrastructures.

The PhD student will contribute to the development of a framework for trustworthy AI for trusted network automation, with a particular focus on defining the characteristics of trustworthy AI in the context of network automation. This includes transparency (interpretable models, explainable AI, causal ML), prediction reliability (uncertainty quantification, conformal prediction, calibration techniques), fairness and bias mitigation, energy-efficient computation (Green AI), infrastructure security, and privacy-enhancing technologies. Moreover, some focus will be dedicated to enhancing the robustness and trustworthiness of AI models used in network monitoring and control, including the detection and mitigation of adversarial vulnerabilities using techniques such as adversarial training. The PhD student will also contribute to the publication of scientific papers, project deliverables and the organization of related workshops and events.

The PhD student will collaborate and participate in research activities with research teams from across 10 countries, including Germany, Sweden, France, Poland, Canada, Finland, Ireland, Spain, Belgium, the United Kingdom and Siwtzerland, and more than 110 industrial and academic partners including Adtran Networks SE, Fraunhofer Heinrich Hertz Institute (HHI), InfoSim GmbH & Co. KG, TU München, Julius-Maximilians-Universität Würzburg, Technical University Berlin, Chalmers University of Technology, SKOOR AG, DFKI (German Research Center for Artificial Intelligence), Nokia Solutions and Networks GmbH & Co. KG, and Deutsche Telekom AG, among many others.

Responsibilities and activities

• Conduct research in the area of communication networks, with a particular focus on automated network and service management in next-generation (5G/B5G/6G) infrastructures.
• Design, implement, and evaluate advanced machine learning and AI-based solutions, including interpretable, trustworthy, and energy-efficient models for intelligent network monitoring, control, and orchestration. 
• Collaborate actively with academic and industrial partners in an international, multi-disciplinary environment.
• Contribute to the dissemination of research results through high-impact scientific publications, open-source tools, and presentations at international conferences.
• Support the organization of workshops, seminars, and other scientific dissemination activities relevant to the project’s objectives and the broader research community.

Requirements

• Master’s degree in Engineering, Telecommunications, Computer Science, Electronic Engineering, or related fields.
• Previous experience, including through internships or research projects, in areas such as telecommunications and networks.
• Knowledge of 5G network architectures and emerging technologies, as well as familiarity with virtualization and cloud computing tools and technologies.
• Understanding of data analysis, machine learning, and artificial intelligence fundamentals.
• Proficiency in major programming languages such as Python.
• Experience in developing machine learning-based optimization algorithms.
• Strong problem-solving skills, with a proactive and solution-oriented approach, and ability to work in multidisciplinary teams.

We offer

• Fixed-term Full-time PhD position.
• Competitive salary in line with Swiss standards.
• A stimulating job in a young and dynamic research team, actively engaged in national and European research projects.
• The opportunity to participate in research projects and international conferences.
• Access to SUPSI student and staff facilities, and related benefits such as discounts and reduced rates (canteen, gymnasium, kindergarten, etc.).
• Support for international travel to participate in research dissemination and collaboration activities.

Application Process

Applications will only be considered if submitted electronically by 17.09.2025, through the dedicated application form. The following documents, written in English, must be included:

• Curriculum vitae, including a list of publications and, if available, a link to the Master thesis
• A motivation letter, including a brief description of past research experience and future research interests (1-2 pages)
• Copies of three published papers relevant to the position
• Names and email addresses of three reference contacts

For further information, please contact Dr. Omran Ayoub.

Incomplete applications, those submitted to incorrect addresses, or those received after the deadline will not be considered. In addition to the required application documents, further documentation (such as a criminal record certificate or a copy of an identity document) may be requested at a later stage.

Our Commitment

SUPSI believes that the future is shaped by diverse perspectives, unique experiences, and a culture that is equitable, inclusive, and respectful of differences.