Research Associate (Post-Doc) position in Signal Processing for Extremely High Frequency Radar

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Research Associate (Post-Doc) position in Signal Processing for Extremely High Frequency Radar

Organization: 
University of Luxembourg
Country of Position: 
Luxembourg
Contact Name: 
Bhavani Shankar
Subject Area: 
Signal Processing Theory and Methods
Sensor Array and Multichannel
Design and Implementation of Signal Processing Systems
Start Date: 
August 01, 2019
Expiration Date: 
September 15, 2019
Position Description: 

Online Applications only: http://emea3.mrted.ly/28n6x

The University of Luxembourg is a multilingual, international research university.

The Interdisciplinary Centre for Security, Reliability and Trust (SnT) invites applications from PhD candidates in the general area of signal processing for extremely high frequency sensing and communication applications. SnT carries out interdisciplinary research in secure, reliable and trustworthy ICT systems and services, often in collaboration with industrial, governmental or international partners.

Your Role

Position Description:

Radar sensor based driver assistance systems for automotive applications are currently under investigation to increase comfort and safety of drivers.  Presence of radar functionality on multiple cars leads to a network of radar sensors which can be exploited to enhance the environment sensing. An emergent automotive scenario is collaborative sensing, where the cars sense and communicate about the emergency situations (like obstacles, braking, accident etc.). The dynamics of the scenario, e.g., number and position of the cars, preclude a central processing unit there by motivating the network radar. Recent advances in wireless communication technology can be exploited to realize a network radar. Further, due to spectrum allocation trends and requirements of high bandwidth, an investigation of extremely high frequencies, namely mmWave and beyond bands (with a corresponding wavelength of about 1 mm), has been attracting significant attention in both the automotive radar industry as well as the mobile community. Compared to microwaves, operation in higher bands provides access to larger bandwidth enabling higher range resolution and fine details of the targets as well as higher data rates. Besides, the size of system components such as the antennas required to process the such signals reduces drastically; this enables the possibility of accommodating high number of antenna elements on the device to enhance the spatial resolution. Further, their incorporation on a moving platform, e.g., automobile, results in a synthetic aperture radar (SAR) / inverse synthetic aperture radar (ISAR) whose advantages are well documented. However, to explore and exploit the advantages of such network radar systems, several research challenges need to be solved. The research will focus on devising optimization algorithms to enhance the performance of MIMO radar networks in waveform optimization, target detection, classification and localization while leveraging advances in wireless communications.

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

  • Carrying out research in the field of signal processing algorithms for MIMO radar networks in extremely high frequencies co-existing with communications
  • Disseminating results through scientific publications

For further information, please contact us at Mohammad.Alaee@uni.lu or Bhavani.Shankar@uni.lu

Your Profile

Qualification: The candidate should possess an MSc degree or equivalent in Electrical/Electronic Engineering, Computer Science or Applied Mathematics. The successful candidates will join a strong and motivated research team lead by Prof. Björn Ottersten and Dr. Bhavani Shankar in order to carry out PhD.

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

  • Signal processing techniques for distributed sensors
  • Developing scientific algorithms in the fields of mmWave (and beyond) radar signal/image processing
  • Waveform design and optimization algorithms applied to the radar systems
  • Machine/Deep Learning with applications to radar systems including Automatic target classification and recognition algorithms (including CNN and DNN)

and have a  strong background in

  • Optimization theory
  • Linear algebra and statistics
  • Statistical Signal processing

Development skills in MATLAB, is required. Exposure to USRP/SDR implementation and familiarity with LabView, C++, and FPGA programming is considered as an advantage.

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

We offer

The University offers a Ph.D. study program with a Fixed Term Contract up to 3 years in total, pending satisfaction of progress milestones (CDD), full-time (40 hrs/week). The University is an equal opportunity employer. The candidate will work in an exciting international environment.

Further Information

Application should be sent online, in English and should include:

  • Full CV, including list of publications and names (and contact information including email addresses) of three 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. The last date for application is September 15, 2019. Applications will processed as they arrive; early application is highly encouraged. Please apply online here:  http://emea3.mrted.ly/28n6x

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