Mohammad Reza Hesamzadeh
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5 months ago
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Doctoral student in Battery Storage in Electricity Markets KTH Royal Institute of Technology in Sweden
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Expired
Country
Sweden
University
KTH Royal Institute of Technology

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About this position
This doctoral position at KTH Royal Institute of Technology focuses on advancing battery energy storage participation in the Nordic electricity market, supporting the transition to a sustainable, low-carbon energy system. As renewable generation increases, battery storage is crucial for providing flexibility, ensuring system reliability, and improving market efficiency. The project tackles three main challenges: designing market-compatible bidding structures for battery storage that reflect operational constraints, developing tailored financial hedge contracts to manage revenue risks in low-volatility markets, and enabling co-optimization of energy and reserve services using advanced optimization and AI-assisted methods.
The research combines mathematical modeling, electricity market design, and computational optimization, offering the doctoral student opportunities to contribute to both theoretical developments and real-world applications. Collaboration with leading industry partners such as Nord Pool and Fortum is integral to the project, providing valuable industry exposure and practical relevance.
Supervision will be provided by Prof. Mohammad Reza Hesamzadeh and Prof. György Dán (KTH), Prof. Derek Bunn (London Business School), and Prof. Darryl Biggar (Monash University), ensuring a diverse and international academic environment. The position is based in Stockholm, Sweden, at KTH Royal Institute of Technology, a leading technical university renowned for its research and innovation in sustainable energy systems.
Applicants must hold a Master’s degree in Electrical Engineering, Energy Systems, Engineering Physics, Applied Mathematics, Operations Research, or a closely related field. Essential skills include a strong background in mathematical optimization (linear, mixed-integer, or nonconvex), understanding of energy systems and electricity markets, computer programming, and analytical problem-solving. Candidates with backgrounds in mathematics, physics, or computer science and a strong interest in energy systems are encouraged to apply. English proficiency equivalent to English B/6 is mandatory.
Selection criteria emphasize the ability to work independently, collaborate effectively, maintain a professional approach, and analyze complex issues. Experience with stochastic optimization, decomposition methods, large-scale optimization, electricity market design, ancillary services, or flexibility markets is considered advantageous. The position offers full-time employment for up to four years, with a monthly salary according to KTH’s Doctoral student salary agreement and access to employee benefits.
To apply, candidates must submit certified copies of diplomas and grades, proof of language requirements, CV, application letter (maximum 2 pages), and representative publications or technical reports. Applications should be submitted via KTH’s recruitment system by the deadline of June 6, 2026. For further information, contact Prof. Mohammad Reza Hesamzadeh ([email protected]) or Prof. György Dán ([email protected]).
KTH offers a creative and dynamic environment with good working conditions and attractive benefits. Equality, diversity, and equal opportunities are central to KTH’s values. Join KTH to contribute to cutting-edge research and innovation in sustainable energy systems.
Funding details
Available
What's required
Applicants must have a Master’s degree in Electrical Engineering, Energy Systems, Engineering Physics, Applied Mathematics, Operations Research, or a closely related field. A strong background in mathematical optimization (linear, mixed-integer, or nonconvex), good understanding of energy systems and electricity markets, computer programming skills, and strong analytical and problem-solving abilities are required. Candidates with backgrounds in mathematics, physics, or computer science and a strong interest in energy systems are encouraged to apply. English proficiency equivalent to English B/6 is mandatory. Selection criteria include ability to work independently, collaborate, professional approach, and analytical skills. Experience with stochastic optimization, decomposition methods, large-scale optimization, electricity market design, ancillary services, or flexibility markets is considered meritorious.
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