Doctoral Researcher in AI and Quantum-Inspired Optimization for Sustainable Energy Systems

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Aalto University is where science and art meet technology and business. We shape a sustainable future by making research breakthroughs in and across our disciplines, sparking the game changers of tomorrow and creating novel solutions to major global challenges. Our community is made up of 16 000 students and 5 200 employees, including 446 professors . Our campus is in Espoo, Greater Helsinki, Finland. Diversity is part of who we are, and we actively work to ensure our community's diversity and inclusiveness. This is why we warmly encourage qualified candidates from all backgrounds to join our community. We are now looking for a Doctoral Researcher in AI and Quantum-Inspired Optimization for Sustainable Energy Systems Are you passionate about developing AI-based and quantum-inspired solutions for the next generation of sustainable energy systems? We are now looking for a fully funded Doctoral Researcher to work on AI-based and quantum-inspired methods for sustainable energy systems. The position is funded by the Research Council of Finland (RCF) and is part of the project "Smart, Economic, and Sustainable Energy Management of Green Maritime Industry via AI Approaches" (SiGMA). The position is hosted by the Multi-energy System Planning and Operation Research Group at Aalto University School of Electrical Engineering . The research will focus on the modelling, optimization, and operation of AI+Energy systems, integrated energy systems, green hydrogen, ship and port energy systems, and energy-intensive infrastructures such as data centres. The research group is led by Assistant Professor Zhengmao Li and focuses on multi-energy system optimization, AI-driven energy management, green hydrogen integration, and sustainable maritime energy systems. The position will also benefit from the group's ongoing research activities and collaborations, and will provide opportunities to work with academic and industrial partners in Finland and internationally. Your role and goals In this position, your doctoral research will focus on developing AI-based and quantum-inspired methods for the modelling, optimization, and operation of sustainable energy systems. The main application area will be green maritime energy systems, especially ship and port energy systems with integrated electricity, heat, hydrogen, storage, and flexible loads. Your main tasks will include: Developing mathematical, data-driven, and AI-based models for sustainable multi-energy systems. Designing optimization and decision-making methods for system planning, scheduling, and operation. Exploring quantum-inspired optimization methods for selected energy-system problems. Applying the developed methods to case studies related to ship and port energy systems, green hydrogen, smart grids, or other energy-intensive infrastructures. Implementing algorithms and simulation models using Python, MATLAB, Julia, or other suitable tools. Analysing simulation and project data, and validating the developed methods through practical case studies. Preparing scientific publications for international journals and conferences. Your network and team In this position, you will join the Multi-energy System Planning and Operation Research Group at Aalto University School of Electrical Engineering. Your main supervisor will be Assistant Professor Zhengmao Li. You will work closely with: Your supervisor and research group , including doctoral researchers, master's students and research assistants working on energy-system modelling, optimization and AI-based methods. Academic collaborators at Aalto University and partner universities in Finland and abroad. Industrial and societal stakeholders , especially in areas related to energy systems, hydrogen, maritime operations, smart infrastructure and data-driven decision-making. The wider Aalto community , including researchers and students from electrical engineering, automation, computer science and energy-related fields. The working style of the group is collaborative and research-oriented. You will be encouraged to develop independent scientific ideas, discuss your work regularly with the team, contribute to joint publications and participate in project meetings, seminars and stakeholder activities. Your experience and ambitions Candidates should hold a Master's degree in electrical engineering, energy systems, automation, or a related field. A strong background in energy-system modelling, mathematical optimization, machine learning, reinforcement learning, or data-driven decision-making is appreciated. Experience with programming and computational modelling is important for the position. Familiarity with Python, MATLAB, Julia, or similar tools is considered valuable. Previous experience in one or more of the following areas is an advantage: power and energy systems, integrated multi-energy systems, hydrogen systems, maritime or port energy systems, data centre energy management, smart grids, stochastic optimization,

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