KTH Royal Institute of Technology invites applications for a doctoral student position in Smart and resilient microgrids, located in Stockholm, Sweden. This PhD project is situated within the third-cycle subject of Electrical Engineering and is funded by the Wallenberg AI, Autonomous Systems and Software Program (WASP), Sweden’s largest research initiative in AI and autonomous systems. The project aims to advance the development of smart and resilient microgrids, which are essential for integrating renewable energy, supporting electrified transport, and enhancing local energy system resilience. Microgrids are complex cyber-physical systems, combining power electronics, communication infrastructure, and software-based control, and are increasingly vital for the transition to sustainable, carbon-neutral energy systems.

The research direction will be tailored to the selected candidate’s expertise, with options including novel algorithm design (advanced control, optimization, deep reinforcement learning) or hardware-oriented development (converter control, experimental validation). The methods developed will be applicable to large-scale, power converter-dominated grids. The successful candidate will join the WASP graduate school, which offers interdisciplinary training, research visits, and networking opportunities with partner universities, industry, and leading researchers in artificial intelligence, autonomous systems, and software.

Supervision will be provided by Associate Professor Qianwen Xu. The position is full-time and temporary, with employment renewable up to four years for completion of the doctoral degree. The workplace offers attractive employee benefits and a monthly salary according to KTH’s doctoral student salary agreement. The university is committed to equality, diversity, and providing a creative, dynamic environment for academic growth.

Eligibility requirements include a second-cycle degree (e.g., master’s) or equivalent, with a strong background in at least one of the following: power systems, power electronics, optimization, or deep reinforcement learning. English proficiency equivalent to English B/6 is mandatory. Candidates should demonstrate goal orientation, independence, collaboration skills, and analytical ability. Preference is given to those with strong skills in machine learning/deep reinforcement learning for power systems and coding, or in power electronics and hardware. Personal skills are emphasized in the selection process.

Applications must be submitted via KTH’s recruitment system and include a CV, application letter with research statement and future research plan, and representative publications or technical reports. The deadline for applications is January 9, 2026. For further information, contact Associate Professor Qianwen Xu at [email protected].

For more details about the WASP program, visit https://wasp-sweden.org/. To apply, use the application link: KTH Application Portal.