27.02.2023, Wissenschaftliches Personal
The newly established Professorship of Energy Management Technologies at TUM’s School of Engineering and Design is looking for Research Associates / Doctoral Candidates (f/m/d) in Machine Learning Applications to Sustainable Energy Management. You are passionate about applying cutting-edge information technology to solve the energy and climate crisis and would like to work in a vibrant research environment? Then let’s design the energy systems of the future together!
Our Research Focus
The researchers working at the newly established Professorship of Energy Management Technologies are focusing on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and prototypical systems controlling complex energy systems like electric grids and thermal systems for a sustainable future. These systems 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
You will work on key research projects within the context described above. The Professorship of Energy Management Technologies closely collaborates with other Professorships at TUM, industry partners, and partner research institutions. You support us in making this cooperation 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. You help us to prepare teaching material, serve as teaching assistant in our lectures, support lab courses, and supervise student research.
Your Profile