PhD position "Agentic AI for Resource Management and Resilient Operations in 6G"

Job description: PhD position "Agentic AI for Resource Management and Resilient Operations in 6G"

• FTE: 1.0

Join the frontier of innovation in 6G: the future of mobile networks technology! In the Netherlands, a unique alliance of 60 top-notch ICT companies, semiconductor firms, and research institutions has united to spearhead specific aspects of 6G: (1) software antennas, (2) AI-driven network software, and (3) groundbreaking 6G applications. Join us as a PhD student in this prestigious Future Network Services (FNS) flagship project, where research and entrepreneurial pursuits converge.

Future 6G infrastructures will involve multiple specialized AI agents that manage radio, transport, computing, and service resources across different domains and vendors. Although individual agents may optimize local objectives, their actions can interact, conflict, or compete for shared resources. This PhD will develop learning methods for coordinating such agentic systems under changing network conditions, incomplete information, and operational constraints. The research will build on constrained and optimistic online learning, distributed learning, and online game-theoretic methods. The developed framework will be studied in two main application areas: multi-domain resource management for AI-enabled services, and resilient network operation, including fault diagnosis, root-cause analysis, and autonomous remediation. The methods will be validated through FNS use-cases, network data, and experimental infrastructure in collaboration with industrial partners.

You’ll be joining an internationally diverse and thriving team, providing ample opportunities for riveting sparring and knowledge sharing. Fostering a highly collaborative and friendly atmosphere, we will give you all the support you need to develop and grow. Moreover, as a valued member of the FNS consortium, you can collaborate with various partners in pursuit of integrating your AI/ML techniques into the various 6G PoCs and demos.

Job requerements

Become part of an expansive ecosystem shaping the development of 6G. You will benefit from training in 5G and beyond networks, AI, and software development. Plus, you will gain exclusive access to (1) a state-of-the-art testbed where theory meets real-world application, and (2) an ecosystem that cultivates entrepreneurial endeavours.

Are you ready to challenge yourself? We're seeking candidates who have, or are about to receive, a Master-of-Science degree in a relevant computer science discipline and who like to combine theory with practice. Proficiency in English is essential, as you'll collaborate within a diverse, international community. While a strong background in the field is crucial, what matters as well is your creative flair, motivation, and above all, your passion for comprehensive research!

TU Delft (Delft University of Technology)

Delft University of Technology is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society.

Faculty of Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics. There is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.

Conditions of employment

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from €3204 - €4051 gross per month, from the first year to the fourth year based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.

Knowledge security

As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed.