Would you like to explore the secret of contemporary lithium-ion batteries and modern battery energy storage systems (BESS)? Do you strive to understand the fundamental characteristics of different battery cells, energy storage system integration, and all aspects of BESS applications? Through the development of industrial battery applications and the implementation of cutting-edge monitoring and measurement techniques, this project aims to use the data-driven approach to perform battery state estimation on real-life use cases.
The PhD position is part of the Nordic5Tech (N5T) battery initiative at the 5 Nordic technical universities. Joining the team, you will be one in a pool of prestigious PhD students breaking new ground at the absolute forefront of BESS technology. As part of the N5T program, you will spend up to 6 months external stay at KTH in Stockholm, Sweden.
Responsibilities
Your overall focus will be strengthening the department’s competencies in the intersection between theory and real-world battery application by operating, monitoring, analyzing, modeling, and controlling the modern BESS.
As part of the N5T PhD program, your tasks will be to:
- Work on laboratory test and grid scale applications.
- Pioneer research on live monitoring of active batteries and BESS.
- Develop methodologies and tools related to battery state estimation and prognosis.
- Disseminate your work at conferences and peer-reviewed journals.
- Network with international research bodies, academic institutions, and industry.
- Follow and complete selected courses.
- Assist in teaching courses and co-supervision of BSc and MSc.
Qualifications
MSc graduates with a background in either Engineering, Mathematics, Computer Science, Computer Engineering, Physics, Sustainable Energy, Electro-chemistry, and related disciplines, including hands-on experiences, are encouraged to apply. We are looking for candidates with diverse backgrounds to join our team. You must be a self-motivated and team-oriented person who thrives in a collaborative environment and enjoys working on complex topics.
A successful candidate would ideally fulfill more of the following points:
- Active knowledge of battery and energy storage systems.
- Measurement techniques in field applications and in the laboratory.
- Modeling and simulation skills (batteries, energy systems, electric equivalent circuits).
- Machine learning, statistical analysis, and other contemporary data-driven techniques.
- Computational methods such as optimization, filtering algorithms, predictors, etc.
- Software and coding skills with, e.g., Python, MATLAB, R, C++, Julia, potentially HIL.
- Excellent command of English in speech and writing.
- Good ability to present results orally, experience with preparing scientific papers for journal publications, and demonstrated team-oriented working attitude.
Application procedure
Your complete online application must be submitted no later than 21 April 2025 (23:59 Danish time).
Based on the collective agreement with the Danish Confederation of Professional Associations
