Doctoral researchers in green hydrogen research to LUT University
About this role
Do you want to build expertise in one of the most rapidly evolving fields of the clean energy transition? We are looking for two doctoral researchers to join LUT University's internationally recognised hydrogen research team and contribute to the development of renewable hydrogen production technologies for future energy systems.
The Department of Electrical Engineering is hiring two doctoral researchers for a Research Council of Finland-funded project focusing on optimising the energy efficiency of high-voltage alkaline water electrolysis stacks powered by solar and wind energy. The positions are part of LUT's internationally recognised hydrogen research activities, which combine expertise in renewable energy systems, electrolysis technologies, modelling, optimisation, artificial intelligence, and fluid dynamics.
LUT's hydrogen research team has more than ten years of experience in renewable electricity-based green hydrogen production. The team studies water electrolyser systems from a multidisciplinary perspective and collaborates closely with industry and leading universities in Finland and abroad. Its research has also contributed to the creation of several successful spin-off companies, including Solar Foods, Elstor, and Neovolt.
What your work will be like
In these positions, you will join LUT's hydrogen research group and contribute to the development of more energy-efficient alkaline water electrolysis technologies for renewable hydrogen production. Green hydrogen is expected to play a key role in the transition towards carbon-neutral energy systems, creating a growing need for efficient and scalable production technologies.
As a doctoral researcher, you will conduct high-level scientific research as part of a multidisciplinary team and complete an article-based doctoral dissertation in English within four years. You will participate in research projects and contribute to scientific publications.
Position 1: Modelling and AI-assisted optimisation of electrol