Doctoral student in accelerated solar cell materials exploration
Sustainable energy and accelerated laboratory approaches are two frontier research areas. Improving solar cell stability is key to achieving more efficient and durable energy solutions.
The Department of Industrial and Materials Science at Chalmers University of Technology is recruiting a PhD student to improve solar cells by combining optimization approaches (machine learning/statistics-based) with laboratory synthesis work. The position offers interdisciplinary training, including both experimental and computational work, and is ideal for students interested in the intersection of materials science, machine learning, and laboratory automation.
The position is based in Gothenburg, Sweden. It is fully funded from the start and will last for 4 years, with the possibility of up to 20% teaching duties that may extend the position by up to 1 year.
Key qualifications and skills:
- Proficiency in Python programming
- Experience with machine learning development
- Interest in experimental science and laboratory work
- Background in materials science (e.g., physics, chemistry, or mechanical engineering)
Deadline: March 8th, 2026