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 the following: www.securityandtrust.lu, and https://wwwen.uni.lu/snt/research/sigcom
Doctoral candidate (PhD student): Incorporating Machine Learning Intelligence in Emerging Tactile Internet Applications (M/F)
The successful candidate will join an internationally leading and motivated research group (SigCom) headed by Prof. Björn Ottersten and Prof. Symeon Chatzinotas in order to carry out doctoral research in direction of Incorporating Machine Learning Intelligence in Emerging Tactile Internet Applications including wireless Augmented Reality (AR)/Virtual Reality (VR), teleoperation systems and remote autonomous driving.
The position holder will be required to perform the following tasks:
• Carrying out research in the predefined areas
• Disseminating results through scientific publications
• Presenting results in the well-known international conferences and workshops
For further information, please contact us at email@example.com
The candidate should possess an M.Sc./M.Eng. degree or equivalent in Electrical/Electronic or Telecommunications Engineering or machine learning.
Experience: The ideal candidate should have some knowledge and experience in some of the following topics:
• Ultra-reliable and low-latency communications (URLLC)
• Coexistence of eMBB, mMTC and URLLC Services
• Wireless Internet of Things (IoT)
• Learning-assisted optimization for wireless communication systems
• Haptic communications
• Wireless virtual reality/augmented reality
and be familiar with the principles of
• Machine learning (supervised, unsupervised and reinforcement)
• Deep learning (deep neural network, recurrent neural network, LSTM)
• Optimization theory
• Control theory
• Linear algebra
Programming skills: MATLAB, Python or C++.
Experience of working with one or more of the following ML and data analytics tools/frameworks will be advantageous: TensorFlow, PyTorch, Keras and GreyCat.
Language Skills: Fluent written and verbal communication skills in English are mandatory.
The University offers highly competitive salaries and is an equal opportunity employer.
Applications should be written in English and should include:
• Full CV, including list of publications and names (and contact information including email addresses) of three references
• Transcript of all modules and results from university-level courses taken
• Research statement and topics of particular interest to the candidate (300 words)
All qualified individuals are encouraged to apply.
Deadline for applications: 15th of March 2020.
Early application is highly encouraged, as the applications will be processed upon reception.