The University of Luxembourg is a multilingual, international research University.
The Interdisciplinary Centre for Security, Reliability and Trust (SnT) invites applications from highly motivated PhD candidates in the general area of radio resource allocation for emerging wireless networks within its Signal Processing and Communications (SIGCOM) research group. SnT carries out interdisciplinary research in secure, reliable and trustworthy ICT systems and services, often in collaboration with industrial, governmental or international partners. For further information, you may refer to www.securityandtrust.lu
PhD Position in Network Automation for Non-Terrestrial Networks
The SIGCOM research group is headed by Prof. Symeon Chatzinotas and Prof. Björn Ottersten. The team focuses on signal processing for satellite/wireless communications/networking and radar applications. The research on communications focuses on the formulation, modelling, design, and analysis of future communication networks (beyond 5G) that are capable of supporting new services in a cost efficient manner. In the B5G domain, SIGCOM addresses large antenna systems, multiuser MIMO systems, Non-orthogonal Multiple Access, radio resource management, mmWave beamforming, physical layer security, full duplex systems, wireless power transfer, software defined networking and network automation. In the satellite domain, SIGCOM addresses transceiver design, onboard processing, active antennas, multi-beam processing, optical communications, localization, spectrum monitoring and network performance optimization. The analysis is based on traditional statistical and optimization methods, as well as learning-assisted approaches for offline training and operational system monitoring/control. The communication activities are supported by CommLab, which exploits Software Defined Radios for fast prototyping and demonstration. For further information, you may refer to https://wwwen.uni.lu/snt/research/sigcom
This PhD project will focus on designing optimal network slicing strategies for the non-terrestrial network automation. The design strategies will optimize the flow management for both 1) deterministic network graphs and 2) dynamic network graphs to optimally dimension and isolate the virtual network resources, e.g., link rate, computation and storage capacity, for different services in an online and autonomous fashion.
The successful candidate will work under the supervision of Prof. Symeon Chatzinotas in the context of the ASWELL project https://wwwfr.uni.lu/snt/research/sigcom/projects/aswell_autonomous_network_slicing_for_integrated_satellite_terrestrial_transport_networks.
The position holder will be required to perform the following tasks:
Qualification: The candidate should possess an MSc degree or equivalent in Electronic Engineering, Computer Science or Applied Mathematics.
Experience: The ideal candidate should have knowledge and experience in some of the following topics:
Development skills in MATLAB or C++ are required.
Language Skills: Fluent written and verbal communication skills in English are required.
The University offers highly competitive salaries and is an equal opportunity employer. You will work in an exciting international environment and will have the opportunity to participate in the development of a newly created university.
Application should include:
All qualified individuals are encouraged to apply.
Deadline for applications: as long as we have found a candidate
However, prospective applicants are encouraged to apply as soon as possible since the hiring process is reviewed continuously until filled.
Ref. RCREQ0003303Apprenez-en davantage
|Intitulé||PhD Position in Network Automation for Non-Terrestrial Networks|
|Employeur||University of Luxembourg|
|Job location||6, rue Richard Coudenhove-Kalergi, L-1359 Luxembourg|
|Publié||septembre 15, 2020|
|Date limite d'inscription||Non Spécifiée|
|Types d'emploi||PhD  |
|Domaines de recherche :||Ingénierie des communications,   Communications informatiques (réseaux),   Génie logiciel,   Génie électrique,   Apprentissage automatique,   Traitement du signal,   Électronique  |