PhD Student in Automatic Control with focus on sensor fusion for localization
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This PhD position is part of the ELLIIT research program (https://elliit.se) and focuses on enabling reliable robot situational awareness in challenging and unpredictable environments. The project is grounded in statistical, model‑based methods that combine multi‑object tracking with simultaneous localization and mapping (SLAM). By leveraging semantic information, the aim is to improve data association, handle multiple hypotheses efficiently, and build consistent maps while simultaneously tracking dynamic objects. The overarching goal is to develop robust and scalable methods that enhance a robot’s understanding of its surroundings, with the intention of demonstrating the results in a simplified lab environment. The student will work closely with a twin PhD project at Lund University, which focuses on learning‑based generation of the type of semantic information used in this work.
As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your work may also include teaching or other departmental duties, up to a maximum of 20 per cent of full-time.
Your qualifications
You have a master’s degree in electrical engineering, engineering physics, mechanical engineering, computer engineering, engineering mathematics or have completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses within the subjects mentioned above. Alternatively, you have gained essentially corresponding knowledge in another way. The degree requirement must be met no later than at the time the employment decision is finalized, which occurs when the employment contract is signed.
Furthermore, you must be eager to learn new things and explore the unknown, and you pay attention to details. You must also have strong communication skills in English, both in writing and orally.
Your workplace
The Division of Automatic Control is successfully conducting research as well as postgraduate and undergraduate education within areas such as autonomous systems, complex networks, data-driven modeling, learning control, optimization, and sensor fusion. The division has extensive collaborations both with industry and other research groups around the world.
Read more about the division here: https://liu.se/en/organisation/liu/isy/rt. For more information about ISY, go to: https://liu.se/en/article/open-positions-at-isy.