Research Associate and Doctoral Candidate (f/m/d) in Experimental Energy Informatics
27.03.2026, Academic staff
You are passionate about applying cutting-edge information technology to solve the energy and climate crisis and would like to work in a vibrant and international research environment? Then let’s design the energy management systems of the future together!
Our Research Focus
The researchers working at the Professorship of Energy Management Technologies are focusing on the design and evaluation of innovative data-driven and Machine Learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop novel optimization methods, Machine Learning algorithms, and prototypical Energy Management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable future. These EMS coordinate distributed renewable generation like solar and wind, flexible loads like heat pumps and electric vehicles, and distributed energy storage like stationary batteries and hydrogen storage to maximize energy efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes the evaluation of existing systems, extensive simulation-based analyses, as well as the implementation and validation of algorithm and system designs in real world settings.
Your Tasks
Together with the EMT team, they are building our laboratory for intelligent energy management systems. The laboratory's goal is to provide versatile test facilities for the development and validation of data-driven energy management systems for monitoring and controlling various energy systems. Test facilities are planned in the following areas, among others: active distribution networks, energy disaggregation, building control, and distributed energy storage. The Professorship of Energy Management Technologies closely collaborates with other professorships at TUM, industry partners, and partner research institutions. You will support us in making these cooperations efficient and productive. As Research Associate you will also support our teaching activities in several Bachelor and Master programs offered by the School of Engineering and Design and the School of Computation, Information and Technology. You will help us to prepare teaching material, serve as teaching assistant in our lectures, support lab courses, and supervise student research.
Your Profile
We offer you the opportunity to do research within a team of highly motivated researchers and benefit from the research environment offered by one of the best universities in Europe and worldwide. We support your doctoral dissertation in the research area outlined above. The offered position (pay grade TV-L 13) is initially limited to 2 years. Further employment is possible and intended.
Your Application
We are looking forward to your application until April 20, 2026. Please submit it as one single PDF file via email to applications.emt@ed.tum.de. Your application should contain the following documents:
Data Protection Information
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.
Kontakt: applications.emt@ed.tum.de
You are passionate about applying cutting-edge information technology to solve the energy and climate crisis and would like to work in a vibrant and international research environment? Then let’s design the energy management systems of the future together!
Our Research Focus
The researchers working at the Professorship of Energy Management Technologies are focusing on the design and evaluation of innovative data-driven and Machine Learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop novel optimization methods, Machine Learning algorithms, and prototypical Energy Management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable future. These EMS coordinate distributed renewable generation like solar and wind, flexible loads like heat pumps and electric vehicles, and distributed energy storage like stationary batteries and hydrogen storage to maximize energy efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes the evaluation of existing systems, extensive simulation-based analyses, as well as the implementation and validation of algorithm and system designs in real world settings.
Your Tasks
Together with the EMT team, they are building our laboratory for intelligent energy management systems. The laboratory's goal is to provide versatile test facilities for the development and validation of data-driven energy management systems for monitoring and controlling various energy systems. Test facilities are planned in the following areas, among others: active distribution networks, energy disaggregation, building control, and distributed energy storage. The Professorship of Energy Management Technologies closely collaborates with other professorships at TUM, industry partners, and partner research institutions. You will support us in making these cooperations efficient and productive. As Research Associate you will also support our teaching activities in several Bachelor and Master programs offered by the School of Engineering and Design and the School of Computation, Information and Technology. You will help us to prepare teaching material, serve as teaching assistant in our lectures, support lab courses, and supervise student research.
Your Profile
- Above-average master’s degree in an engineering-related field
- Good software engineering and machine learning skills
- Hands-on mentality with first practical experience in constructing lab hardware and developing innovative software
- Inquisitive and passionate about research and knowledge transfer
- Independent, creative, and committed way of working
- Ability to think conceptually and analytically
- Strong interest in energy technology and systems
- Very good command of English
- Big plus: good command of German
We offer you the opportunity to do research within a team of highly motivated researchers and benefit from the research environment offered by one of the best universities in Europe and worldwide. We support your doctoral dissertation in the research area outlined above. The offered position (pay grade TV-L 13) is initially limited to 2 years. Further employment is possible and intended.
Your Application
We are looking forward to your application until April 20, 2026. Please submit it as one single PDF file via email to applications.emt@ed.tum.de. Your application should contain the following documents:
- Curriculum vitae
- Complete academic transcripts
- Letters of reference from previous positions held, including internships
- Bachelor and Master thesis
Data Protection Information
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.
Kontakt: applications.emt@ed.tum.de