Project Overview
This exciting postdoc position is based within the Vehicle Safety Division and includes close collaboration with the Systems and Control Division, as well as the Department of Mathematical Sciences, and the department of Computer Science and Engineering. In addition, you’ll work alongside key industry partners like Volvo Group, VCC, and ZF.
At the Vehicle Safety Division, we combine expertise in human factors and engineering to identify safety challenges, develop innovative solutions, and assess their impact on traffic safety. Specifically, this postdoc role will focus on improving the efficiency and accuracy of virtual safety assessments within the context of ADS.
The Systems and Control Division focuses on modeling and optimizing complex problems in robotics, electromobility, and autonomous driving. As a postdoc, your role will contribute to efficient optimal control and path-planning solutions that support automated driving systems.
Key Research Areas
In automated driving, perception systems are crucial for perceiving surroundings, localizing vehicles, and facilitating path planning and decision-making processes, which are essential for vehicle control. Perception technology must accurately detect traffic scenarios, and predict the behavior of other road users. Your research will target:
- Sensor Perception Modeling for virtual safety assessments of advanced driver assistance systems (ADAS) and ADS.
- Developing open-source, computationally efficient perception and prediction models.
- Incorporating AI and machine learning techniques to enhance models’ ability to handle various road users in stochastic environments and models’ robustness, especially under rare or challenging traffic scenarios.
- Integrating perception models into the prediction module for optimal, model-based, stochastic control in ADS.
- Utilizing learning-based motion predictors such as Recurrent Neural Networks (RNNs) and transformers, while ensuring safety guarantees such as probabilistic feasibility.
- Conducting sensitivity analyses to evaluate how the models trade accuracy, complexity, and computational efficiency in virtual safety assessments and in model predictive control.
This role provides an opportunity to make significant contributions to the future of autonomous driving by developing perception and prediction models that can operate under real-world conditions while maintaining a high level of safety and performance.
About our department
The Department of Mechanics and Maritime Sciences (M2) is dedicated to shaping the engineers and researchers of tomorrow. Our work is focused on transitioning to a sustainable transport system, addressing major societal challenges, and collaborating with industry to drive impactful change. Our diverse research portfolio spans all modes of transport and contributes to environmentally friendly process technologies and sustainable energy solutions.
Your Major Responsibilities
- Conduct pioneering research on sensor perception modeling for virtual and ADS development.
- Publish high-quality papers and present your findings at international conferences.
- Collaborate across departments and with industry stakeholders to push the boundaries of perception and prediction technology.
- Participate in teaching within educational programs related to the project.
- Engage with both academic and industrial partners to ensure the broader impact of your research.
Qualifications
- A PhD degree in a field relevant to the position is mandatory.
- Extensive experience with programming (for example, Python, Matlab, and/or C++).
- Good writing and oral skills in English.
- You should be comfortable with and good at interacting with others in international projects (across organizations).
- You are expected to be somewhat accustomed to teaching, and to demonstrate good potential within research and education.
If you have experience of working with sensor modeling, vehicle dynamics and sensor data (specifically time-series data), and/or experience with pre-crash virtual safety assessment, that is highly meritorious.
*To qualify for the position of postdoc, you must hold a doctoral degree awarded no more than three years prior to the application deadline (according to the current agreement with the Swedish Agency for Government Employers). The date shown in your doctoral degree certificate is the date we use, as this is the date you have met all requirements for the doctoral degree. Exceptions from the 3-year limit can be made for longer periods resulting from parental leave, sick leave or military service.
Knowing Swedish is not a requirement but Chalmers offers Swedish courses.
Contract terms
This postdoc position is a full-time temporary employment for two/three years.
We offer
Chalmers offers a cultivating and inspiring working environment in the coastal city of Gothenburg.
Read more about working at Chalmers and our benefits for employees.
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 20240576 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.
Please note: The applicant is responsible for ensuring that the application is complete. Incomplete applications and applications sent by email will not be considered.
Application deadline: 2024-11-19
For questions, please contact:
Researcher, Jordanka Kovaceva, Vehicle Safety, jordanka.kovaceva@chalmers.se, +46-31-772-1266
Prof., Jonas Bärgman, Vehicle Safety, jonas.bargman@chalmers.se. +46-31-772-5846
Prof., Nikolce Murgovski, Systems and Control, nikolce.murgovski@chalmers.se, +46-31-772-4800
Collaborators in the project are
Associate Prof. Lars Hammarstrand from Electrical Engineering
Prof. Ann-Brith Strömberg from Mathematical Sciences
Associate Prof. Chih-Hong Cheng from Computer Science and Engineering.
*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***
