Master Thesis – open application

About Acconeer

Acconeer is a young and innovative company developing the world´s smallest 60 GHz radar based on research from Lund University. The Acconeer radar sensors combines extremely low power consumption with sub-mm distance estimation accuracy. It enables distance measurements, micro-motion detection, material classification and much more, all within a sensor sized 5×5 mm including antennas.

Acconeer is located in a brand-new office in Västra Hamnen, Malmö. We are currently a group of around 50 people with high R&D focus, working closely together over the R&D disciplines – hardware, software, and algorithm research. We have a large and growing international customer base in the automotive, consumer electronics, industrial and IoT segments which means our sensors are integrated in everything from cars and robotic lawn mowers to industrial tank-level gauges and touchless buttons for smart cities.

Interested in doing a Master Thesis at Acconeer?

Research is at the core of everything we develop at Acconeer, and we have continuous collaborations with universities within all of our fields: Analog and Digital ASIC, hardware integration, embedded programming, and algorithm research. These are some of our earlier master theses:

Customization of Ibex RISC-V Processor Core

Optimizing Machine Learning Inference for MCU:s

On the statistics and practical application of the reassignment method for Gabor spectrograms

Hand Gesture Classification using Millimeter Wave Pulsed Radar

Here are some of the current ideas of what a Master Thesis at Acconeer could include. If it sounds interesting, or if you have your own idea, apply and we´ll start a discussion.

Near skin vital signs

Research the possibilities for very near-body measurements of primarily heart rate and blood pressure with low power radar. Use signal processing and optimize near-sensor measurements to detect sub-skin movements.

Posture and human activity classification

Research and evaluate human body behaviour with radar measurements from one or more radar components. Use signal processing and machine learning to classify posture and activity, for example walking versus biking, as part of our ongoing smart city project.

Radar test system

Acconeer uses robots to move radar targets in different positions for automated testing and quality assurance. New innovative test setups could be studied and tested in order to measure for example speed or long ranges super-accurately.

Mapping and object detection

Research the next steps in using object detection algorithms such as SAR for mapping and localization (SLAM). Work on methods for robots to understand its surroundings. This could include:

• Sensor fusion – use sensors like gyros, accelerometers and cameras to create large virtually antennas.
• Rotating radar – push the limits on how well and efficient a rotating radar or radar reflector can map the surrounding environment.