3 PhD positions on AI-networking Delft University of Technology, Faculty Electrical Engineering, Mathematics and Computer Science
3 PhD positions on AI-networking
Department/faculty: Faculty Electrical Engineering, Mathematics and Computer Science
Faculty Electrical Engineering, Mathematics and Computer Science
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. A weblink to the press release is
https://overons.kpn/nl/nieuws/2018/kpn-en-tu-delft-gaan-samenwerken-aan-nieuwe-ict-technologieën
Job description
We have 3 PhD openings defined on the following themes:
1. AI-networking: decisions and clustering
The ability to accurately discover all hidden relations between items that share similarities is paramount to solving large optimization problems that pertain to artificial intelligence and networking. By embedding our recently developed clustering techniques into reinforcement learning problems, we will optimize several processes within KPN that relate to learning, decision taking, recommendation giving, and prediction making.
Supervisors: Jaron Sanders and Piet Van Mieghem; Network Architectures and Services (NAS)
More information: nas.ewi.tudelft.nl, jaronsanders.nl
2. AI-networking: control and network science
Based on network state information (e.g. in routers), the network’s dynamic process is identified using system’s theory and new learning methods in order to control and manage the telecom network.
Background: network science, systems theory, telecommunications, stochastic processes
Supervisors: Bart De Schutter (3ME, DCSC) and Piet Van Mieghem (NAS)
More information: nas.ewi.tudelft.nl, www.dcsc.tudelft.nl
3. AI-networking: data and network science
Automatic recommendation of operation choices to network/system components (e.g. which content, service, or resource to allocate) when the system is subject to heterogeneous and dynamic user demand.
Background: network science, data science (recommender systems, machine learning, time series analysis), complex systems
Supervisors: Huijuan Wang and Alan Hanjalic; Multimedia Computing Group
More information: http://www.mmc.tudelft.nl
Requirements
We are looking for brilliant PhD candidates with a strong interest to the join a university-company collaboration on future Networking. The specific desired background per theme is listed above.
Because of project definitions, we are looking for EU citizens.
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
To apply, please e-mail a detailed CV along with a letter of application by Augus 15, 2018 to Lotte Ophey at HR-EEMCS@tudelft.nl, with a clear choice for only 1 of the three themes above.
When applying for this position, please refer to vacancy number EWI2018-22a.
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