Research Associate and Doctoral Candidate (f/m/d) in Wind Power Forecasting using Machine Learning
20.08., Academic staff
The Professorship of Energy Management Technologies at TUM’s School of Engineering and Design is looking for a Research Associate and Doctoral Candidate (f/m/d) in Energy Informatics, specifically for a DFG project in wind power forecasting using machine learning.
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- 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 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:
You will work on a DFG-funded project on wind power forecasting using machine learning, which we are carrying out together with the Chair of Wind Energy. 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:
1. Above-average master’s degree in computer science or a closely related field
2. Very good software engineering and machine learning skills
3. Hands-on mentality with first practical experience in developing innovative software
4. Inquisitive and passionate about research and knowledge transfer
5. Independent, creative, and committed way of working
6. Ability to think conceptually and analytically
7. Strong interest in energy technology and systems
8. Very good command of English
9. Big plus: good command of German
Our offer:
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.