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Machine Learning Based Radar Detector
  • Python
  • Machine Learning
  • Matlab
  • Deep Learning
Sony Electronics
120 days ago

We look for the risk-takers , the collaborators , the inspired and the inspirational . We want the people who are brave enough to work at the cutting edge and create solutions that will enrich and improve the lives of people across the globe. So, if you want to make the world say wow, let's talk.

The conversation starts here. If this role matches your ambitions and skillset, let's get started with your application . Take a look at our other open positions too. Our many opportunities can lead to infinite possibilities .

SONY is one of the most innovative companies in the world and drives the development of technology in a global network of research institutions ahead. The Stuttgart Technology Center (STC) was founded in 1989. With the Stuttgart Laboratory 1 (SL1) and the Stuttgart Laboratory 2 (SL2), the STC is a home for two important research and development offices in this network. As part of the European organization of Sony (SEU), the STC plays an important role in the worldwide network of the Research and Development Center (RDC) Sony.
Stuttgart Laboratory 1 conducts research in the areas of "Computational Imaging, Perception Systems, RF Communications, Artificial Intelligence and Speech & Sound Processing." The results of the research will define the core technologies for future products and new business opportunities for Sony.

Radar team of SL1 has been developing signal processing software for several SONY radar prototypes. The software includes the algorithms that process radar data starting from raw radar cubes all the way to detection and tracking results. Good performance of the overall algorithm chain was confirmed both for simulated and real radar data.

The latest version of SL1 radar signal processing software implements conventional algorithms for radar detection and Angle-of-Arrival (AoA) estimation. Recently, several publications disclosed a new approach to solving these radar problems. Namely, to solve them by means of Machine Learning (ML) or Deep Learning (DL) methods.

We would like to understand the benefits and limitations of this approach in context of SONY radar applications (e.g. automotive Short, Medium, and Long Range Radar).

Therefore, the targets of this student project are:

  • Implement ML or DL based radar detector according to SL1 radar API specification
  • Compare performance of the ML/DL radar detector to that of conventional processing available in SL1 radar signal processing software

Some of the tasks include:

  • Do literature search on the topic and write a summary document
  • Implement ML or DL based radar detector according to SL1 radar API specification
  • Compare performance of the ML/DL radar detector to that of conventional processing available in SL1 radar signal processing software
  • Document the work and results
  • Write monthly reports
  • Prepare and give weekly presentations
  • Write final report, prepare final presentation


  • Mathematics: Linear Algebra, Statistics, Probability Theory, etc.
  • Background: Signal Processing (radar, communication, image processing, etc.), Machine Learning, Deep Learning, Neural Networks
  • Programming: MATLAB, Python
  • General: curiosity, risk-taker, quick learner, able to tackle practical problems, good command of spoken and written English

We offer:

  • Opportunity to work in an international team
  • Chance to apply your skills and theoretical knowledge in cutting-edge research activities
  • learning more about state-of-the-art technology in your field of interest
  • a compensation of 1000€ gross per month plus support for local transportation and lunch
  • Position is fulltime and for maximum 6 months

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