KTH Royal Institute of Technology is offering a fully funded PhD position in the area of smart and resilient microgrids, supervised by Associate Professor Qianwen Xu. The research focuses on developing advanced methods for microgrids using machine learning (including deep reinforcement learning), power electronics, and control theory to ensure stability, security, and resilience under various disturbances. The project is part of the Wallenberg AI, Autonomous Systems and Software Program (WASP), Sweden’s largest research initiative in AI and autonomous systems. The PhD project aims to support the energy transition and a carbon-neutral society by enhancing microgrid technology for renewable energy integration, electrified transport, and local resilience. Candidates can pursue research in either novel algorithm design (advanced control, optimization, deep reinforcement learning) or hardware-oriented development (converter control, experimental validation). The research will also extend to large-scale power converter-dominated grids, addressing the challenges of modern, cyber-physical energy systems. Applicants should have a strong background in power systems, power electronics, optimization, or deep reinforcement learning, and must meet the English proficiency requirement (English B/6). The selection process values goal orientation, perseverance, independence, collaboration, and analytical skills. The position is fully funded, with a monthly salary and benefits according to KTH’s doctoral student salary agreement. The employment is full-time for up to four years, with annual or biannual renewal, and tuition is covered. To apply, candidates must submit a CV, an application letter with a research statement and future research plan, and representative publications or technical reports. Applications are accepted through KTH’s recruitment system until January 9, 2026. For more information, visit the official job posting or contact Associate Professor Qianwen Xu at [email protected]. Keywords: smart microgrids, resilient microgrids, machine learning, deep reinforcement learning, power electronics, power systems, advanced control, energy transition, renewable energy integration, cyber-physical systems.

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 .