PhD position: AI-based Resource Management of Deterministic QoS for (beyond) 5G Networks (EWI2019-49)

Updated: 20 days ago

PhD position: AI-based Resource Management of Deterministic QoS for (beyond) 5G Networks

Department/faculty: Faculty Electrical Engineering, Mathematics and Computer Science
Level: University Graduate
Working hours: 36-38 hours weekly
Contract: <empty>
Salary: 2325 - 2972 euros monthly (full-time basis)


Faculty Electrical Engineering, Mathematics and Computer Science

Ranked the 52nd best university in the world, according to the QS World University Rankings® 2019, Delft University of Technology excels in civil engineering, mechanical engineering and electrical engineering. The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) is known worldwide for its high academic quality and the social relevance of its research programmes. The faculty’s excellent facilities accentuate its international position in teaching and research. Within this interdisciplinary and international setting the faculty employs more than 1100 employees, including about 400 graduate students and about 2100 students. Together they work on a broad range of technical innovations in the fields of sustainable energy, telecommunications, microelectronics, embedded systems, computer and software engineering, interactive multimedia and applied mathematics. 

Delft University of Technology and KPN, the leading fixed and mobile telecom operator in The Netherlands, have started a collaboration, called NExTWORKx. Goals of this collaboration include excellent academic research into both fundamental properties and implementation of the next generation telecommunication networks. In the first phase of the collaboration, 6 PhD students, daily supervised by experts in both TUDelft and KPN, will focus on themes that are relevant for KPN in order to design and manage the network of the future using promising technologies as Artificial Intelligence (AI), 5G and Blockchain. 

Click here to read the press release.

The Networks Architectures and Services (NAS) section, part of the Department of Quantum & Computer Engineering in EEMCS, educates and conducts research in the broad area of complex networks, ranging from data communications and Internetworking, to other man-made infrastructures such as road-traffic networks, and to biological, brain, social, and financial sector networks. The emphasis lies on design and management of infrastructures. NAS also has expertise in concepts (e.g. routing, robustness) of network architectures, in the performance analysis of quality of service-aware protocols and Internet behaviour, and in strategic and business-oriented challenges for network operators.


Job description

The research is motivated by 5G (and beyond) telecommunications. Those future, mobile networks are being developed to offer innovative services in domains such as Media & Entertainment (virtual 3D reality), Automotive/Mobility, e-Health and Smart Industry (machine-to-machine communications). The plethora of services are characterized by widely varying traffic characteristics and often highly challenging Quality of Service (QoS) requirements in terms of throughput, latency, packet loss and/or reliability. Moreover, a high degree of user/device mobility and arduous propagation conditions further challenge QoS offering per service or traffic flow.

The goal of the project is to design an architecture and self-learning algorithms that can optimise and guarantee deterministic QoS of individual traffic flows whilst maximizing network resource efficiency. The general QoS architecture for end-to-end communication of heterogeneous types of traffic will include routing and scheduling for each traffic type and admission control possibly with QoS renegotiations and with shaping and spacing. Ideally, the performance of the proposed QoS architecture will be evaluated by using stochastic modelling and queuing theory, in addition to simulations that will complement the mathematical analysis. Employing AI/ML methodologies are strongly encouraged.


Requirements

We are looking for a brilliant PhD student who has experience in AI/machine learning techniques. The ideal candidate is multidisciplinary, well-versed in probability theory, algorithms, network science, with a background in telecommunications. An open mind for a university-company collaboration on this novel 5G theme is an advantage.


Conditions of employment

TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children’s Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. 

As a PhD candidate you will be enrolled in the TU Delft Graduate School. TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills. Please visit www.tudelft.nl/phd for more information. 


Information and application

For more information about this position, please contact Prof. dr. ir. P. Van Mieghem, P.F.A.VanMieghem@tudelft.nl .

To apply, e-mail a detailed CV along with a letter of motivation by 1 October 2019 to P.F.A.VanMieghem@tudelft.nl with CC to Marjolein van der Heijden (hr-eemcs@tudelft.nl ).  

When applying for this position, please refer to vacancy number EWI2019.49 

Enquiries from agencies are not appreciated.


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