Industrial PhD Student 4D Radar for Autonomous Driving

About Sensrad

At Sensrad we build and develop one of the worlds most advanced radar sensors. Our sensor provides measurements of its surroundings containing thousands of four-dimensional detections in each frame delivering a radar image of the environment with a uniquely high resolution. This in combination with the fact that a radar works in any weather and light condition has sparked great interest among customers. We supply a variety of verticals ranging from heavy vehicles and drones to static installations surveilling high-value infrastructure and intelligent traffic management. Today we have customers in all these areas located all over the world.

Currently we are looking for an industrial PhD student which in collaboration with our partner Örebro University conducts research which explores 4D imaging radar as a foundation for enabling autonomous operations in mining and construction vehicles to drive safely in all conditions.

The Project

The industrial PhD project described here is part of REEDEAM a new graduate school led by Mälardalen University together with Örebro University and Luleå University of Technology. The program will train 15 PhD students as future technical leaders in areas such as automation digitalization metallurgy and energy collaboration with leading companies including Epiroc LKAB Minerals Bosch Rexroth Kanthal RISE and Sensrad REEDEAM aims to support Swedish heavy industry in reducing carbon emissions and driving the green transition.

The initiative builds on the REEDEAM Competence Development project and strengthens the link between academia and industry creating long-term impact in carbon-free metallurgy AI and automation and circular industry solutions.

Your Role

As an Industrial PhD student you will research implement and evaluate radarcentric odometry localization and SLAM algorithms and integrate them into multimodal perception stacks for autonomous vehicles. The project targets autonomous driving for offroad and industrial settings (e.g. off-highway mining and construction). You are expected to publish the research findings in top signal processing and robotics conferences and journals. Moreover you will collaborate with Sensrad engineers and university representatives to help transition your research into products.

Required qualifications

To qualify for the position you must have

• A masters degree in electrical engineering computer engineering applied physics robotics or equivalent.

• Be proficient in spoken and written English.

• Solid skills in computer programming (Python / C)

• Experience with signal processing and perception algorithms (such as deep machine learning and Bayesian statistics methods.)

Meritorious qualifications

• Experience with 4D imaging radars.

• Knowledge about state estimation and SLAM methods.

• Research publications or open-source contributions.

What we offer

We offer a unique opportunity to push the frontier of radar-centric autonomy on real applications and real deployments. You will work with a cutting-edge 4D radar sensor on diverse platforms and in challenging environments. Moreover at Sensrad we have an international team and modern facilities. You may also travel to test sites and partner labs for collaboration and we have a close collaboration with academia.

Supervision and Enrollment

This is an industrial PhD position co-supervised by Sensrad and Örebro Univeristy. Enrollment terms and coursework follow the universitys doctoral program requirements. The expected duration is five years where 80% of the time is dedicated for research contributions and 20% on activities at Sensrad. The position is in Gothenburg but the student is expected to travel frequently to Örebro to collaborate with the research partner and to participate in courses at the university. This is a paid employment and is fully funded from the start.

How to apply

Please submit the following information:

• CV

• Degree transcripts (. and .)

• Personal letter; introduce yourself describe your previous relevant experience and your future goals and research focus.

• Contact information for two references.
• Submit your application no later than November 1st.

Apply for this position via the career portal at .