Publisher
source

Sasan Sadrizadeh

Top university

4 months ago

Postdoctoral researcher in advanced control of AI-based energy systems KTH Royal Institute of Technology in Sweden

Degree Level

Postdoc

Field of study

Computer Science

Funding

Available

Deadline

Expired

Country flag

Country

Sweden

University

KTH Royal Institute of Technology

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Where to contact

Official Email

Keywords

Computer Science
Environmental Science
Mechanical Engineering
Electrical Engineering
Artificial Intelligence
Simulation Training
Civil Engineering
Energy Engineering
Energy Efficiency
Cost Analysis
Thermal Energy Storage
Automatic Control
Model Predictive Control
District Heating
Heat Pump
Machine learning

About this position

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].

Funding details

Available

What's required

Applicants must hold a doctoral degree or an equivalent foreign degree in Energy Technology, Building Services, Building Physics, Civil or Architectural Engineering, or a closely related field, to be completed by the time of employment. Required expertise includes advanced control (such as Model Predictive Control, adaptive or optimal control), AI or machine learning, and extensive experience in building energy system simulation. Candidates should have a strong background in energy system design, optimization, and control, solid understanding of electricity and district heating pricing structures, and strong programming skills for implementing and testing optimization and control algorithms. Experience in teaching and supervision at bachelor's and master's levels is expected. Excellent written and spoken English is required. 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.

How to apply

Log into KTH's recruitment system and submit your application by the deadline. Include your CV, publication list, doctoral degree certificate, a brief research statement (max 2 pages), and contact information for at least two referees. Ensure your complete application does not exceed 6 pages and is received by midnight CET/CEST on the last day of application.

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