Sasan Sadrizadeh
Dr. at KTH Royal Institute of Technology
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About
Dr. Sasan Sadrizadeh is an academic at KTH Royal Institute of Technology in Sweden. His research focuses on fluid dynamics, indoor air quality, and energy efficiency, as reflected in his recent articles on unsteady airflow modeling, ventilation systems, and the health implications of indoor environments. Dr. Sadrizadeh employs numerical simulations and machine learning techniques to optimize thermal energy systems and assess the impacts of air quality in various settings.
Positions (1)
Sasan Sadrizadeh
KTH Royal Institute of Technology
11 months ago
This postdoctoral position at KTH Royal Institute of Technology offers an exciting opportunity to contribute to the digital and sustainable transformation of building energy systems. The research focuses on developing and applying advanced control strategies and AI-driven optimization methods to improve the design, operation, and cost-effectiveness of both building- and district-level energy systems. Key areas of investigation include predictive and adaptive control, data-driven optimization, and intelligent energy management of thermal systems, all aimed at achieving clean, efficient, and cost-effective heating and cooling production. The project will explore how advanced control and optimization can reduce operating costs, mitigate peak electricity and heating demand, and enhance system flexibility and resilience. Integration of renewable energy sources, thermal storage, sector coupling, and heat pump technologies are central to the research. The successful candidate will be responsible for developing models and simulations in advanced software environments, publishing high-quality scientific papers, and collaborating with international research groups, industry partners, and energy providers. Applicants must have a doctoral degree in a relevant field such as Energy Technology, Building Services, Building Physics, Civil or Architectural Engineering, or a closely related discipline. Required skills include expertise in advanced control (e.g., Model Predictive Control, adaptive or optimal control), AI or machine learning, and extensive experience in building energy system simulation. A strong background in energy system design, optimization, and control, as well as a solid understanding of electricity and district heating pricing structures, is essential. Programming skills for implementing and testing optimization and control algorithms are required, along with experience in teaching and supervision at bachelor's and master's levels. Excellent communication skills in English are mandatory. Preferred qualifications include a doctoral degree obtained within the last three years, a strong publication record, experience with district heating/cooling integration, thermal energy storage, renewable energy systems, and the ability to work independently and collaboratively in international research environments. The position is full-time, temporary, and offered for up to three years, with a monthly salary and attractive benefits. KTH provides a creative and dynamic environment, emphasizing equality, diversity, and equal opportunities. Applications must be submitted via KTH's recruitment system by November 10, 2025, and should include a CV, publication list, doctoral degree certificate, a brief research statement, and contact information for at least two referees. For further information, contact Dr. Sasan Sadrizadeh at [email protected].
11 months ago
Articles (11)
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2025
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2023
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2023
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2022
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2022
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2022
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2022
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2022
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2022
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2022
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2022
Collaborators (6)
Bjarne W. Olesen
Technical University of Denmark
Amirmohammad Behzadi
KTH Royal Institute of Technology
Hassan Abbas Khawaja
Associate Professor
UiT The Arctic University of Norway
Fuzhan Nasiri
Concordia University
Parastoo Sadeghian
KTH Royal Institute of Technology
Christophe Duwig
KTH Royal Institute of Technology
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