Postdoctoral Researcher in RF Situational Awareness (m/w/d)

Kurzüberblick

• Standort: Kirchberg Campus
• Arbeitsmodell: Vollzeit
• Anstellungsart: Festanstellung

Aufgaben

• Conduct research on RF threat modelling and vulnerability assessment for satellite communications links
• Design, implement, and evaluate AI/ML-based algorithms for real-time detection, classification, and localization of jamming and spoofing signals using time-frequency-space domain features extracted from I/Q data, e.g. STFT, wavelets, Wigner-Ville
• Contribute to simulation of jamming environments in the 6GSPACE Lab using SDR/USRPs/RFSoC boards, generating synthetic training datasets and extracting robust features for SIGINT and spectrum-monitoring pipelines
• Develop and integrate TDOA/FDOA-based geolocation methods into RF situational-awareness workflows for interference source localization
• Participate in field data-collection and validation campaigns, adapting models to real-world data and assessing their robustness and real-time feasibility
• Support the design and assessment of anti-jamming and counter-interference strategies, including AI-enabled mitigation and multi-connectivity/link-diversity schemes for resilient satellite communications links
• Publish results in leading international journals and conferences and contribute to project deliverables and the technology roadmap for future anti-jamming capabilities

Anforderungen

• A PhD degree in Telecommunication Engineering, Electrical Engineering, Computer Science, or a closely related field, with a focus on wireless communications, RF signal processing, and/or applied machine learning
• Strong background in digital communications and RF signal processing, ideally with experience in SATCOM, NTNs, or space-borne SIGINT / spectrum monitoring applications
• Demonstrated experience in at least one of the following: interference / jamming detection and classification, spectrum monitoring and I/Q data analysis, TDOA/FDOA-based localisation or DOA estimation, design of ML models for time-series or signal data
• Excellent programming skills in Python and/or MATLAB for signal processing and ML. Familiarity with libraries such as NumPy, SciPy, PyTorch or TensorFlow
• Experience with C/C++ and GPU/accelerator platforms is an asset
• Hands-on experience with software-defined radio platforms, RF measurement equipment, or laboratory testbeds is highly desirable
• Previous involvement in collaborative or publicly funded research projects
• A solid publication record in relevant IEEE conferences or journals will be considered a strong asset
• High level of autonomy, strong analytical and critical-thinking skills, and the ability to work effectively in a multidisciplinary and multicultural team with industrial partners
• Fluency in English is required

Benefits

• Multilingual and international character. Modern institution with a personal atmosphere. Staff coming from 90 countries. Member of the "University of the Greater Region" (UniGR)
• A modern and dynamic university. High-quality equipment. Close ties to the business world and to the Luxembourg labour market. A unique urban site with excellent infrastructure
• A partner for society and industry. Cooperation with European institutions, innovative companies, the Financial Centre and with numerous non-academic partners such as ministries, local governments, associations, NGOs …

Wie Sie sich bewerben

• Curriculum Vitae
• Cover letter detailing your motivation for applying to the advertised research topic and/or project, including how your background, interests, and career goals align with its objectives
• Transcript of all modules and results from university-level courses taken