PhD Candidate in Automatic Control within WASP | |
Published | |
Workplace | Linkoping, Östergötland, Sweden |
Category | |
Position | |
Linkoping Reference number LiU-2025-00513 We have the power of over 40,000 students and co-workers. Students who provide hope for the future. Co-workers who contribute to Linköping University meeting the challenges of the day. Our fundamental values rest on credibility, trust and security. By having the courage to think freely and innovate, our actions together, large and small, contribute to a better world. We look forward to receiving your application! We are now looking for a PhD candidate in Automatic Control, at the Department of Electrical Engineering (ISY), to be admitted to the WASP graduate school. Your work assignmentsIn this WASP financed project you will be working with statistical multi-object tracking based on audio and visual data. You will be using the current advancements in machine learning based object detection and classification to extract meaningful information from the data. This information will then be used to maximize the performance and reliability of multi-object tracking using statistical tracking methods. The project will be carried out in collaboration with WARA-PS ( ?url=https%3A%2F%2Fportal.waraps.org%2F&module=jobs&id=3048634" target="_blank" rel="nofollow">?url=https%3A%2F%2Fportal.waraps.org%2F&module=jobs&id=3048634" target="_blank" rel="nofollow">https://portal.waraps.org/ ). This gives the possibility to collect and work with unique experimental data to verify the algorithms developed in the project. Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden’s largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. Read more: ?url=https%3A%2F%2Fwasp-sweden.org%2F&module=jobs&id=3048634" target="_blank" rel="nofollow">?url=https%3A%2F%2Fwasp-sweden.org%2F&module=jobs&id=3048634" target="_blank" rel="nofollow">https://wasp-sweden.org/ The graduate school within WASP is dedicated to provide the skills needed to analyze, develop, and contribute to the interdisciplinary area of artificial intelligence, autonomous systems and software. Through an ambitious program with research visits, partner universities, and visiting lecturers, the graduate school actively supports forming a strong multi-disciplinary and international professional network between PhD-students, researchers and industry. Read more: ?url=https%3A%2F%2Fwasp-sweden.org%2Fgraduate-school%2F&module=jobs&id=3048634" target="_blank" rel="nofollow">?url=https%3A%2F%2Fwasp-sweden.org%2Fgraduate-school%2F&module=jobs&id=3048634" target="_blank" rel="nofollow">https://wasp-sweden.org/graduate-school/ As a PhD candidate, you devote most of your time to doctoral studies and the research project of which you are part. Your work may also include teaching or other departmental duties, up to a maximum of 20% of full-time. Your qualificationsYou 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 topics mentioned above. Alternatively, you have gained essentially corresponding knowledge in another way. Furthermore, you shall be eager to learn new things and explore the unknown, and you like to pay attention to details. You must also have strong communication skills in English, both in writing and orally. The project will include work with demonstrator platforms, hence you should have experience of programing and working with hardware. Your workplace | |
| |
In your application, please refer to myScience.org and reference JobID 3048634. |
Related News
4 February 2025
Flipping the Script: Inverse-Design as Game-Changer in Physics
31 January 2025
Bringing machine learning into the real world
29 January 2025
New study improves the trustworthiness of wind power forecasts