Doctoral Program

Who are we?
Volvo Cars is a company on a mission; to bring traditional car manufacturing into a connected, sustainable and smart future.
Since 1927, we have been a brand known for our commitment to safety, creating innovative cars that make life less complicated for our consumers. In 2010, we decided to transform our business, resulting in a totally new generation of cars and technologies, as well as steady growth and record sales. Today, we’re expanding our global footprint in Europe, China and the US, and we’re on the lookout for new talent.

Background and main responsibilities
Machine Learning (ML) has shown large potential for solving problems intractable by classical methods. These include pattern recognition in unstructured data such as images, a key enabling technology for e.g., automated driving. It has also been shown to be a useful tool for other types of various data analysis tasks within the automotive domain.

Due to their stochastic nature, using ML components requires specific approaches related to the architectural design and verification/validation of the electrical system of the vehicle. Suitable architecture containing both stochastic and traditional deterministic components shall be defined which assures safety, robustness, fault tolerance, and the exchange of data between ML components and the rest of the vehicle. Furthermore, the nature of ML algorithms makes them difficult to test and analyse from a safety perspective, which requires implementation of specific verification and validation methods. 
In order to address the above-mentioned needs, this project aims to:
•    Define and evaluate different architectural styles and patterns for developing systems with ML components and exchange of extracted information between their independent subsystems.
•    Develop methods for validation and verification, enabling use of ML for safety relevant vehicle systems with high accuracy and availability requirements.
•    Investigate data quality and dataset composition in order to develop optimised AI models for automotive. 
In the short term, the project is expected to contribute to the development of safe, robust and fault tolerant electrical systems with ML components in vehicles. In the long run, the project is expected to contribute to the continuous deployment of ML components to different autonomous subsystems in cars, and their safe and reliable utilization in the transportation eco-system.
As part of the Volvo Cars Industrial PhD Program (VIPP), you are expected to conduct research in the area of architectural design and verification/validation of systems with machine learning components, in order to address the above defined objectives. This involves close collaboration with the software and electronics design and verification teams and complete vehicle data science dep. 
You will also collaborate with other researchers within the VIPP program at Volvo and academia. The academic affiliation will be at the Software Engineering division at the Dept. of Computer Science and Engineering at Chalmers | University of Gothenburg (UGOT).
The position is permanent. You are expected to meet objectives of the VIPP project and get your PhD degree within 4-5 years of full-time work (~80% research and ~20% related industrial work). You will have both industrial (at Volvo Cars) and academic (at Chalmers | UGOT) supervisors. Also, you are Expected to publish the results in 8-10 publications in international journals and conferences.
Who Are You?
We are looking for a curious person that are hungry to constantly learn and develop. You have a positive attitude and enjoy being part of a team. We also believe that you enjoy communicating and dare to speak in front of large audiences.
It is necessary to be organized and structured in following up your work independently when needed. We expect you to take responsibility for tasks and to drive them until successful completion. You are committed to achieve your objectives but open for modifications when needed. 
Required for the role is:
•    M.Sc. within computer science, software electronics, data science or equivalent.
•    Good programming skills and experience in working with machine learning algorithms.
•    Good understanding of machine learning theory and algorithms.
•    Good knowledge of architectural design patterns and strategies.
•    Good understanding of system verification techniques, testing and quality assurance.
•    Experience in the development of large systems is meritorious.
Application and contact
We have a continuous selection process so we recommend that you submit your application in English as soon as possible, but no later than 2022-04-22. Note that we do not accept applications via e-mails. If you have any questions regarding the position, please contact: 
Darko Durisic (darko.durisic@volvocars.com), Product Manager – Complete Electrical System Architecture
Ashok Chaitanya Koppisetty (ashok.chaitanya.koppisetty@volvocars.com), Technical Specialist & Architect (industrial supervisor)
For questions regarding the recruitment process, please contact Divyashri Prakash Kartik (divyashri.prakash.kartik@volvocars.com)