University of Luxembourg
2 weeks ago
Doctoral Researcher in Advanced Communications University of Luxembourg in Luxembourg
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Country
Luxembourg
University
University of Luxembourg

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About this position
The University of Luxembourg, a leading international research university, is offering a PhD position for a Doctoral Researcher in Advanced Communications within the Interdisciplinary Centre for Security, Reliability and Trust (SnT). The Signal Processing and Communications (SIGCOM) research group at SnT is renowned for its work in secure, reliable, and trustworthy ICT systems, with a strong focus on innovation and collaboration with industry partners. SIGCOM's research spans high-performance mobile and satellite communications, including 5G/6G telecommunications, satellite-based internet connectivity, and advanced experimental facilities such as 6GSpaceLab, CommLab, HybridNet Lab, QCI Lab, TelecomAI Lab, and CSAT Lab.
The doctoral researcher will contribute to one or more of SIGCOM's four strategic research areas: radio frequency transceiver design, optical communications, quantum communications, and system-level design and optimization. Research topics include hardware and waveform design (e.g., reconfigurable intelligent surfaces, flexible antennas, power amplifiers, advanced modulation techniques), resource allocation and security (e.g., secure communications, jamming resilience), photonics and free-space optics, next-generation optical communications (e.g., Li-Fi, adaptive optics), quantum computing and networking (e.g., quantum error correction, quantum key distribution), and AI-driven system-level optimization (e.g., Edge AI, Telecom GPT, integrated sensing and communications).
Applicants must hold an M.Sc. or M.Eng. degree in telecommunication engineering, signal processing, machine learning, or a closely related field in electronic, electrical, or computer engineering. Candidates should have at least one published work in prestigious journals or conferences, preferably Q1 journals or top-tier venues. Experience or knowledge in topics such as 5G/6G wireless communications, wireless IoT, UAVs, resource allocation and optimization, joint communications and sensing/PNT systems, network virtualization and slicing, MAC protocols, multi-antenna signal processing, graph signal processing, machine learning (supervised, unsupervised, reinforcement), deep learning, neuromorphic computing, optimization theory, stochastic geometry, and strong programming skills in MATLAB, Python, JULIA, or C++ is required. Language proficiency at B2 level in the thesis language is mandatory.
The University of Luxembourg offers a modern, multilingual, and international environment, with high-quality equipment and close ties to industry and European institutions. The position is a fixed-term contract for 36 months, full-time (40 hours/week), based at the Kirchberg Campus. The yearly gross salary for every PhD at the University of Luxembourg is EUR 41976 (full time). The university promotes an inclusive culture and encourages applications from individuals of all backgrounds.
Applications should be submitted online through the HR system, including a CV, cover letter, transcript of university-level courses, and a research statement (max. 1 page). Early application is encouraged as applications are processed upon reception. Applications by email will not be considered.
Funding details
Available
What's required
Applicants must hold an M.Sc. or M.Eng. degree in telecommunication engineering, signal processing, machine learning, or a closely related field in electronic, electrical, or computer engineering. Candidates should have at least one published work in prestigious journals or conferences, preferably Q1 journals or top-tier venues. Experience or knowledge in topics such as 5G/6G wireless communications, wireless IoT, UAVs, resource allocation and optimization, joint communications and sensing/PNT systems, network virtualization and slicing, MAC protocols, multi-antenna signal processing, graph signal processing, machine learning (supervised, unsupervised, reinforcement), deep learning, neuromorphic computing, optimization theory, stochastic geometry, and strong programming skills in MATLAB, Python, JULIA, or C++ is required. Applicants must demonstrate at least B2-level proficiency in the language of their thesis, with accepted certificates as per university guidelines.
How to apply
Submit your application online through the HR system, including your CV, cover letter, transcript of university-level courses, and a research statement (max. 1 page). Early application is encouraged as applications are processed upon reception. Applications by email will not be considered.
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