Research Associate and Doctoral Candidate (f/m/d) in Experimental Energy Informatics

Overview

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. Let’s design the energy management systems of the future together!

Our Research Focus

The researchers at the Professorship of Energy Management Technologies focus on the design and evaluation of innovative data-driven and Machine Learning-based systems to integrate more renewable energy into energy systems and to make energy use more efficient. We develop novel optimization methods, Machine Learning algorithms, and prototypical Energy Management systems (EMS) that control complex energy systems such as buildings, electricity distribution grids, and thermal energy systems for a sustainable future. These EMS coordinate distributed renewable generation (solar, wind), flexible loads (heat pumps, electric vehicles), and distributed energy storage (stationary batteries, 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 evaluating existing systems, extensive simulation-based analyses, and the implementation and validation of algorithm and system designs in real-world settings.

Your Tasks

Together with the EMT team, you will help build 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 areas such as 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 the cooperations to be efficient and productive. As a Research Associate you will also support teaching activities in Bachelor and Master programs offered by the School of Engineering and Design and the School of Computation, Information and Technology. You will help prepare teaching material, serve as teaching assistant in 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

Our Offer

We offer 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 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

The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance.

Data Protection Information

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