This postdoc position will expose you to one of the most challenging and exciting problems in motion planning and control of autonomous vehicles. You will be given the unique opportunity to access an exclusive combination of datasets and experimental infrastructure and collaborate with a mixed academic and industrial research team leading the development of cutting-edge autonomous driving technologies.
Project description
The successful candidate will join a team of Ph. D. students, engaged in neighboring research, and is expected to contribute to the design of learning and prediction algorithms for humans’ behavior in traffic. If possible and relevant, the achieved results will be demonstrated through experiments on full-scale vehicles and in collaboration with our industrial partners.
The research project is in collaboration with Ericsson and Zenuity and is strongly connected with ongoing research projects within the WASP (Wallenberg Autonomous Systems Program).
Information about the division and the department
We invite applications for one post-doctoral position in Mixed model- and learning-based prediction of human road users. At the Mechatronics Group of the Electrical Engineering Department, we are engaged in both fundamental and applied research related to intelligent transportation systems. Ongoing research projects focus on the design and the experimental validation of predictive motion planning and control algorithms for autonomous vehicles operating in complex urban traffic.
Major responsibilities
In this research project, you will lead a team of international Ph. D. students in a research project in collaboration with industry. You will coordinate the efforts in both the theoretical development and understanding of prediction tools and their deployment on experimental setups.
The working time of post-doctoral staff is mainly devoted to research. Undergraduate teaching duties, not exceeding 20% of the working time, may include supervision of MSc students. The appointment is a full-time employment (not a scholarship) for a period of not more than two years (1+1).
Qualifications
A PhD (or close to completion) in system identification, machine learning, control theory or neighboring relevant field with focus on machine learning and data analysis qualifies you for this position. The PhD degree should be awarded no more than three years prior to the application deadline (according to the current agreement with the Swedish Agency for Government Employers). Experience in automotive control applications will be preferred.
Ability to initiate new research collaborations is essential. Good communication skills in oral and written English are required. Swedish is not a requirement but Chalmers offers Swedish courses.
Contract terms
This postdoc position is a full-time temporary employment for two years.
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Chalmers aims to actively improve our gender balance. We work broadly with equality projects, for example the GENIE Initiative on gender equality for excellence. Equality and diversity are substantial foundations in all activities at Chalmers.
Application procedure
The application should be marked with Ref 20220657 and written in English. The application should be sent electronically and be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system does not support Zip files.
CV: (Please name the document as: CV, Surname, Ref. number) including:
• CV, include complete list of publications
• Previous teaching and pedagogical experiences
• Two references that we can contact.
Personal letter: (Please name the document as: Personal letter, Family name, Ref. number)
1-3 pages where you:• Introduce yourself• Describe your previous research fields and main research results• Describe your future goals and future research focus
Other documents:
• Attested copies of completed education, grades and other certificates.
Use the button at the foot of the page to reach the application form.
Application deadline: 31 August, 2023
For questions, please contact:
Research Professor, Paolo Falcone, Division of Systems and Control
E-mail: falcone@chalmers.se
Phone: +46317721803
Professor Jonas Sjöberg, Division of Systems and Control
E-mail: jonas.sjoberg@chalmers.se
Phone: +46317721855
*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***
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