PhD candidate in Risk-aware Multiagent RL-based Resource Management for Multilayer Ground-Air-Space Networks

University of Luxembourg
December 22, 2022
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Offerd Salary:Negotiation
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Contract Type:Fixed Term Contract
Working Time:Full time
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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.

The SIGCOM research group is headed by Prof. Symeon Chatzinotas, and mainly carries out research activities in the areas of signal processing for wireless communication systems, including satellite communications, and is currently expanding its research activities towards quantum information systems. Use cases of interest include IoT verticals, unmanned aerial vehicles, integrated satellite-space-terrestrial networks, quantum communications and key distribution, spectrum management and coexistence, tactile Internet, and autonomous transportation. Furthermore, our activities are experimentally driven and supported by the SDR CommLab, the S DN Lab, the 5G-Space Lab, our SW Simulators, and our OTA Facilities. For further information, you may refer to https: // wwwen.uni.lu/snt/research/sigcom

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

This is a fully funded position for 4 years. The successful candidate is expected to work on the design of autonomous, safe and efficient collaborative transmission strategies based on Risk-aware Multiagent Reinforcement Learning for multilayer Ground-Air-Space 6G networks. The design strategies will be optimized for 1) RAN resource allocation, 2) 3D mobility management and 3) risk minimization to guarantee constraints in dynamic environment. The research question is how to optimally design distributed communication strategies at every network node to safely and timely serve heterogeneous service types under highly dynamic environment. This will provide an efficient and distributed execution strategy for multi-agent systems under limited and error-prone communication networks, while fulfilling the vertical services requirements.

The successful candidate will work under the supervision of Dr. Thang X. Vu and join a strong and motivated research team lead by Prof. Symeon Chatzinotas.

The position holder will be required to perform the following tasks:

  • Work on an emerging research topic of Multiagent Reinforcement Learning- based Resource Management for multi-layer ground-air-space networks
  • Carry out research in the areas: i) Radio resource allocation, ii) 3D mobility and flow management, and iii) Risk-minimization for constrained optimization
  • Contribute to the National FNR CORE project “ RUTINE : Distributed and Risk-aware Multi-Agent Reinforcement Learning for Resources and Control Management in Multilayer Ground-Air-Space Networks”
  • Disseminate results through scientific publications in the top-tier venues
  • Present results in top-tier international conferences and workshops
  • Your Profile

    Qualification: The candidate should possess a Master degree in Electrical Engineering, Computer Science, or equivalence.

    Experience: The ideal candidate should have some knowledge and experience in a number of the following topics:

  • Background in general wireless communications. Experience in one of following areas is an advantage: multiuser and multiantenna systems, unmanned aerial vehicle, task/goal/semantic-based communications
  • Radio resource allocation/ Radio resource management (e.g., bandwidth and power allocation, scheduling, etc)
  • Experience in machine learning (both theory and application) and/or multiagent reinforcement learning is an advantage
  • Optimization techniques and tools: convex optimization, successive convex approximation
  • Programming skills in MATLAB are required. Experience in Python is an advantage
  • 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!

  • Complete picture of the perks we offer
  • Discover our Partnership Programme
  • In Short
  • Contract Type: Fixed Term Contract 36 Month (extendable up to 48 months if required)
  • Work Hours: Full Time 40.0 Hours per Week
  • Employee and student status
  • Location: Kirchberg
  • Job Reference: UOL05413
  • The yearly gross salary for every PhD at the UL is EUR 38028 (full time)

    How to apply

    Applications should be submitted online and include:

  • Full CV, including:
  • For each degree received or currently enrolled in, provide the degree, institution name, institution city and country, and date (or expected date) of graduation. Include the title and short summary of your final (Bachelor / Master) Thesis if you did one.
  • List of publications (if any)
  • Name, affiliation and contact details of two referees
  • Transcript of all modules and results from university-level courses taken
  • Cover letter with motivations and topics of particular interest to the candidate (approx. 1 page)
  • All qualified individuals are encouraged to apply.

    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.

    About the University of Luxembourg

    University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The University was founded in 2003 and counts more than 6,700 students and more than 2,000 employees from around the world. The University's faculties and interdisciplinary centres focus on research in the areas of Computer Science and ICT Security, Materials Science, European and International Law, Finance and Financial Innovation, Education, Contemporary and Digital History. In addition, the University focuses on cross-disciplinary research in the areas of Data Modelling and Simulation as well as Health and System Biomedicine. Times Higher Education ranks the University of Luxembourg #3 worldwide for its “international outlook,” #20 in the Young University Ranking 2021 and among the top 250 universities worldwide.

    Further information

    For further information, please contact Dr. Thang X. Vu at thang.vu@uni.lu

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