Industrial PhD Student: Digital Twin for Energy Prediction

Industrial PhD Student: Digital Twin for Energy Prediction


Position Description
Are you passionate about engaging in research to solve scientific problems within the area of Electromobility on a topic with great industrial significance? If yes, keep on reading!


Here, is a great opportunity for a PhD on Digital Twin for Energy Prediction within the Electromobility Department, where the future is already in progress and cutting edge technical solutions, products, and services come to life. This exciting research project will be carried out through close collaboration with the Automatic Control group at Chalmers University of Technology.


This is us, your new colleagues at Electromobility
We belong to the department of Electromobility, within Volvo Group Trucks Technology. We design and develop complete electric propulsion systems and components, such as energy storage, motor drives and charging systems with special focus on technology creation for various Volvo Group products. Our team is agile, truly customer oriented, working closely together to drive the development of new technologies.


Besides the vehicle itself, Volvo provides productivity services to its customers in order to improve the use of their fleets. At our section, we are accountable for the energy prediction algorithms, from advanced engineering and research to product development. These algorithms are at the core of many current and future digital services.


Main Role and Responsibilities
Energy consumption prediction is an essential enabler for fleet management services of electric trucks. Route and charge planning are examples of those. However, it is a complex problem that depends on several aspects, such as speed and topography, but also uncertain factors such as weather conditions and driver behavior. There is still room for increasing the accuracy of the predictions by using machine learning techniques together with a digital twin, a virtual representation of the vehicle. The main challenges that this PhD project will address are formulating the digital twin model and designing the machine learning methods to estimate energy consumption of electric trucks. Your major responsibility is to pursue research in line with the project, publish and present scientific articles, support the Volvo Group patent strategy, and take part in discussions for knowledge sharing. You will continuously contribute to our future technologies and products by bridging the existing knowledge gaps through your novel ideas and research results.


This exciting research project will be carried out in close collaboration with the Electrical Engineering division at Chalmers University of Technology. The division has a well-established research group with special focus on Electromobility. The position is at Volvo and you will be working in close cooperation with researchers, experts, and developers along with scientific supervision both at Volvo and Chalmers.


Who are you?
You need to have strong collaboration, networking, and complexity management skills. You also need to be open-minded, self-motivated, and meticulous with independent critical thinking in your problem solving approach. We also believe you are a person who feels enthusiastic about machine learning methods with a solid theoretical foundation to design physics-aware models. You are a person who gets thrilled to explore the unknown and drive new ideas forward under uncertainty. In addition, we believe you have the following:
Strong master level educational background in electrical engineering, computer science or similar, with special interest in core courses related to machine learning and control theory.
Fluent in both written and spoken English.
Proficiency in Matlab and Python.

Any experience with vehicle dynamics or electromobility systems will be meritorious.


What can we offer?
We can guarantee that you will get great opportunities to work together with highly skilled colleagues from different cultures in an exciting and challenging environment, helping you to develop professionally. We firmly believe that conducive work environment based on trust, transparency, empowerment, and flexibility is utmost important to feel happy and thrive at work leading to our mutual success. We believe that we can drive prosperity together only by sharing knowledge and through teamwork.


We strongly believe that teams with a high level of diversity give a great competitive edge and can make a real difference through close cooperation and teamwork.




Do you find it exciting and you believe this perfectly matches your future ambitions and passion?
Please, send your application including the following mandatory documents:
Full CV including your academic background, professional experiences, main technical competences/skills, and two references with contact information
Cover Letter (1-2 pages) including your short background, previous relevant R&D experience, research interests, motivation for this Industrial PhD position, and future professional goals.
Attested copies of transcript of grades for both bachelor and master courses
Abstracts of your bachelor and/or master thesis with web links to full text.

Additional documents if available:
a. Two publications or project technical reports
b. Special certificates (like TOEFL, IELTS, etc.)
c. Letter of Recommendations


If you have any questions regarding this research project and the position, please do not hesitate to contact us. We will be glad to give you more information.


Contact:
Dr. Rafael Basso, Systems Engineer – Productivity Services,
Department of Electromobility
Volvo Group Trucks Technology, Gothenburg, Sweden
+46 (0)31 323 5834, rafael.basso@volvo.com


Kindly note that due to GDPR, we will not accept applications via mail. Please use our career site.