Doctoral student in Data-driven AI based Battery Aging Modeling KTH Royal Institute of Technology in Sweden

The KTH Royal Institute of Technology invites applications for a doctoral student position in Data-driven AI based Battery Aging Modeling. This opportunity is part of the ALTBESS project, funded by the Swedish Energy Agency, which aims to advance battery energy storage system (BESS) operation in buildings integrated with photovoltaic (PV) systems. The project is designed to support the transition toward smarter and more sustainable building energy systems by leveraging real-world case studies and combining simulation, optimization, and operational data.

The doctoral student will focus on developing battery aging models tailored to specific case studies using transfer learning and data-driven techniques. These models will be integrated into existing optimization and scheduling frameworks to enable aging-aware battery operation. The research will culminate in a user-friendly software package suitable for researchers and practitioners, facilitating the adoption of advanced battery management strategies in the energy sector.

This position offers a unique opportunity to work at the intersection of artificial intelligence, energy system optimization, and battery technologies. The research environment is highly collaborative, involving both academic and industrial partners, and is situated within a leading international technical university committed to sustainability and innovation.

Supervision will be provided by Dr Farzin Golzar. The position is full-time and includes a monthly salary according to KTH’s doctoral student salary agreement, along with employee benefits. The employment is temporary, with the possibility of renewal, and is based in Stockholm, Sweden.

Applicants must have a master’s degree or equivalent, with completed coursework in energy systems and optimization methods. Experience or interest in machine learning, data analysis, battery modeling, sector coupling, and optimization methods is advantageous. English proficiency equivalent to English B/6 is required. Selection will emphasize personal skills, including the ability to work independently and collaboratively, professional approach, and analytical capabilities.

To apply, submit your application through KTH’s recruitment system by March 12, 2026. Required documents include a CV, application letter, certified copies of diplomas and grades, proof of language requirements, and representative publications or technical reports. For further information, contact Dr Farzin Golzar at [email protected].

KTH offers a creative and dynamic environment with good working conditions, attractive benefits, and a strong commitment to equality, diversity, and sustainability. Join us in shaping the future of energy technology and battery research.