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PhD in Energy Efficient AI/ML for Wireless Communications

Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg
Luxembourg (Canton), Luxembourg
Closing date
7 Jul 2024

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Computing, Engineering
Job Type
PhD Position
Employment - Hours
Full time
Fixed term

Job Details

About the SnT

SnT is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services. We play an instrumental role in Luxembourg by fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent.

SnT is active in several national projects funded by National Research Fund (FNR) and local industries, and international research projects funded by the EU FP7 programme, H2020 programme and the European Space Agency (ESA). For further information, you may check:

The SigCom research group carries out research activities in the areas of signal processing for wireless communication systems including satellite communications and radar systems and is currently expanding its research activities in exploring several emerging use cases of next generation wireless communications systems. For details, you may refer to the following:

The University of Luxembourg is seeking to hire a highly motivated and an outstanding researcher in the area of optimization performance of interference-limited wireless communication systems for its Interdisciplinary Centre of Security and Trust (SnT), within the Signal Processing and Communications (SigCom) research group, led by Prof. Björn Ottersten and Dr. Symeon Chatzinotas.

We're looking for people driven by excellence, excited about innovation, and looking to make a difference. If this sounds like you, you've come to the right place!

Your Role

The PhD position is related to a new national project entitled BrainSat. The project focuses on integrating neuromorphic computing technologies into satellite communications to address the inefficiencies of current SatCom systems, which are characterized by high latency and power consumption. By deploying neuromorphic processors that emulate the functionality of the human brain, the project aims to drastically reduce energy requirements by up to 100,000 times compared to traditional computing. This reduction enables enhanced on-board processing capabilities for real-time data handling and autonomous operations, improving operational responsiveness and quality of service (QoS). Incorporating AI and machine learning algorithms, the neuromorphic processors will enable advanced predictive analytics and adaptive decision-making capabilities, further optimizing satellite performance.

The position holder will be required to perform the following tasks

  • Contribute to the BrainSat project by
    • Defining promising use-cases for the AI/ML neuromorphic model application
    • Generating / obtaining training data (e.g. using SIGCOM tools such as SW simulators)
    • Running data analytics, neuromorphic models Training and Testing & comparison with non-neuromorphic models
    • Implementation and comparison in neuromorphic and non-neuromorphic hardware
    • Participating in outreach events related to general AI, inspiring young generations to be interested in AI-related topics
  • Attend and contribute to the project meetings with SES
  • Disseminate results through scientific publications
  • Present results in well-known international conferences and workshops

Your Profile

Qualification: The candidate should possess an M.Sc./M.Eng. Degree in Telecommunication Engineering, signal processing, or a closely related field in Electronic, Electrical and Computer Engineering

Experience: The ideal candidate should have a strong background in wireless communication. In addition, a background and interest in a number of the following areas is required

  • Wireless and mobile communications. Background on Non terrestrial communications is considered a plus
    • Knowledge of terrestrial wireless radio resource optimization techniques is considered an advantage
  • Mathematical Tools: The candidate should have knowledge in a number of the following tools used for the analysis and optimization of communication networks
    • Convex/non-convex optimization
    • Machine learning: supervised, unsupervised, and reinforcement learning considered a plus
    • Signal processing
  • Programming skills in MATLAB are required, and is considered an advantage in Python
  • Good oral presentation skills: The candidate will be required to present and defend his/her work in front of wide audience of experts

Language Skills: Fluent written and verbal communication skills in English are required

Here's what awaits you at SnT

  • A stimulating learning environment. Here post-docs and professors outnumber PhD students. That translates into access and close collaborations with some of the brightest ICT researchers, giving you solid guidance
  • Exciting infrastructures and unique labs. At SnT's two campuses, our researchers can take a walk on the moon at the LunaLab, build a nanosatellite, or help make autonomous vehicles even better
  • The right place for IMPACT. SnT researchers engage in demand-driven projects. Through our Partnership Programme, we work on projects with more than 55 industry partners
  • Multiple funding sources for your ideas. The University supports researchers to acquire funding from national, European and private sources
  • Competitive salary package. The University offers a 12 month-salary package, over six weeks of paid time off, meal vouchers and health insurance
  • Be part of a multicultural family. At SnT we have more than 60 nationalities. Throughout the year, we organise team-building events, networking activities and more
  • Boost your career. Students can take advantage of several opportunities for growth and career development, from free language classes to career resources and extracurricular activities

But wait, there's more!

How to apply

Applications should be in English and include

  • Curriculum Vitae, including
    • Contact address
    • For each degree received or currently enrolled in, provide the degree, institution name, institution city and country, and start date and date (or expected date) of graduation. Include the title and short summary of your and Bachelor / Master Thesis if you did one
    • In case of previous publications: List of publications (authors, title, journal/conference name and date of publication). Provide a link in case of open access
    • Name, affiliation and contact details of three referees
  • Cover letter with motivations and topics of particular interest to the candidate (approx. 1 page)

All qualified individuals are encouraged to apply. For further Information, please contact Flor Ortiz ().

Early application is highly encouraged, as the applications will be processed upon reception. Please apply formally through the HR system. Applications by email will not be considered.

The University of Luxembourg embraces inclusion and diversity as key values. We are fully committed to removing any discriminatory barrier related to gender, and not only, in recruitment and career progression of our staff.

General information:

  • Contract Type: Fixed Term Contract 36 Month
  • Work Hours: Full Time 40.0 Hours per Week
  • Location: Campus Kirchberg
  • Employee and student status
  • Job Reference: UOL06559

The yearly gross salary for every PhD at the UL is EUR 40952 (full time)


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