Industrial PhD on Causal Machine Learning for Condition Monitoring

Scania is now undergoing a transformation from being a supplier of trucks, buses and engines to a supplier of complete and sustainable transport solutions.

Are you interested in helping to shape the technology of tomorrows transport system?


At Scania R&D, within the Connected System unit, we work with the future's sustainable transport system and the connected vehicle. Our responsibility is to ensure that data from the vehicles can be used by the various connected services, to generate as much customer value as possible. You get a key role in shaping tomorrow's smart diagnostic system on the connected fleet. Within the scope of an industrial PhD Scania R&D, together with KTH driving forward research on intelligent predictive maintenance services.

Pursuing industrial doctoral studies at KTH and Scania means devoting yourself to a research project under the supervision of experienced researchers from university and industry. You will follow an individual study plan, take courses within a doctoral program and write a thesis. As an industrial PhD student, you will be employed at Connected Systems department in Scania and devote 80% of your time to research at KTH and 20% to non-related research activities at Scania R&D.

The research project

The project spans over several disciplines, such as AI, machine learning, edge computing, causal inference, communication protocols, computer systems, condition monitoring, anomaly detection, and diagnostics. It has elements of both basic research (e.g., developing new machine learning and causal inference methods) and applied research (e.g., adapting to, deploying, and evaluating those methods on heavy vehicles).
The overreaching goal is to develop causal machine learning models for vehicle components using operational sensor data. The developed methods will need to be robust, easy to understand and to generalize well under the hardware and connectivity constraints found in heavy vehicles. In addition, your task will include demonstrating the developed methods on already existing hardware infrastructure.

Your Profile

As a person, you are pragmatic and communicative, with a genuine technical interest. You are goal-oriented and like challenges. You have a high-quality focus and like to be at the forefront.

You have an academic education at university level (Master of Science Degree) in physics, electrical engineering, mathematics, computer science or equivalent. You communicate fluently in English, in both speech and writing.

It is expected that the applicant:
• is eligible for doctoral studies at KTH, in specific having a Master of Science degree in an area relevant to the project
• has extensive skills in computer science, data science, and programming
• has taken university level courses in mathematics, statistics, algorithms, complex systems, machine learning and artificial intelligence
Previous experience in applied research projects and within the automotive industry is of advantage.


Contact

Katarina Prytz
Applications will be open until July 31 or until the vacancy is filled.
Starting date August 1st. 2021.


Scania is a world-leading provider of transport solutions. Together with our partners and customers we are driving the shift towards a sustainable transport system. In 2020, we delivered 66,900 trucks, 5,200 buses as well as 11,000 industrial and marine power systems to our customers. Net sales totalled to over SEK 125 billion, of which over 20 percent were services-related. Founded in 1891, Scania now operates in more than 100 countries and employs some 50,000 people. Research and development are mainly concentrated in Sweden. Production takes place in Europe and Latin America with regional product centres in Africa, Asia and Eurasia. Scania is part of TRATON GROUP. For more information visit: www.scania.com.