The Interdisciplinary Centre for Security, Reliability and Trust (SnT) is carrying out interdisciplinary research in secure, reliable and trustworthy ICT systems and services, often in collaboration with industrial, governmental or international partners. The SIGCOM group in SnT is pursuing research on automotive radar applications in partnership with IEE (www.iee.lu), a Luxembourg based global leader in automotive safety sensing systems for occupant detection and classification. Recently, Prof. Bjorn Ottersten Director of SnT and head of SIGCOM, has been awarded the prestigious European Research Council (ERC) Advanced Grant to pursue research on cognitive radar systems with applications to automotive radar. A new research project funded by the Luxembourg government (FNR) on ``Signal processing for next generation radar’’. The position is planned to start in May 2020. For further information, you may check: www.securityandtrust.lu and http://wwwen.uni.lu/snt/research/sigcom
The SIGCOM research group is in a unique position towards realizing the objectives of the project having exposure to radar signal processing through ongoing research projects, evolution of communication standards through participation and contribution as well as experience with prototype chip sets from the test-bench development activity.
As novel applications emerge, the requirements on radar systems have grown significantly from being “a blip on the radar”, to providing an image like reconstruction of the surroundings. Currently, multistatic and widely-separated MIMO radars offer multiview perspective. However, these systems suffer from the need for high rate synchronization, lack of performance guarantees, minimal exploitation of advances in waveform processing and machine learning among others. Thus, it is essential to go beyond the mature co-located MIMO and the current widely-separated MIMO radars towards achieving reliable imaging like performance for extended targets. In fact, many of these networks, like the automotive can involve large number of dynamic nodes. This necessitates devising novel radar-network architectures as well as exploring various optimization methodologies for waveform design, super-resolution parameter estimation and decentralized resource allocation.
This emerging field opens interesting avenues for pursuing research in radar signal processing and joint radar-communication for distributed sensors, especially on
• Developing robust signal processing for distributed radars
• Relevant architectures for novel radar networks including high level information exchange mechanisms for identified use cases
• Associated signal-processing elements including development of optimization algorithms for waveform and receiver design as well as their adaptation to dynamic scenarios
Qualification: The candidate should possess (or be in the process of completing) a master degree or equivalent in Electrical/Electronics Engineering, Computer Science or Applied Mathematics.
Experience: The ideal candidate should have good theoretical background in a number of the following topics:
- Optimization methodologies with application to Radar Systems
- Widely-separated MIMO Radar System, Waveform Design and Receiver processing
- Statistical Signal Processing and knowledge about modelling with differential equations
Development skills in MATLAB is required and exposure to the latest radar technology and digital communications is desirable.
Language Skills: Fluent written and verbal communication skills in English are required.
The University offers a Ph.D. study program with an* Initial contract of 14 months, renewable for up to 36 months, with a further possible 1-year extension if required*, full-time (40 hrs/week). The University offers highly competitive salaries and is an equal opportunity employer. The candidate will work in an exciting international environment.
Application: Application should be sent online, in English and should include:
• Full CV, including list of publications, bachelor/master thesis and names (and contact information including email addresses) of 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. The University of Luxembourg is an equal opportunity employer.
Deadline for applications: The last date for application is January 31, 2020. Applications will be processed as they arrive; early application is highly encouraged.