Student Assistant (f/m/d): Machine Learning in Energy Management

11.10.2026, Student assistants, internships, student research projects

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 Professorship of Energy Management Technologies focuses 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:

• Supporting the design and implementation of research infrastructure, in particular a novel platform for machine learning models in the energy sector
• Working on machine learning projects being conducted at the professorship, e.g., renewables forecasting and grid state estimation
• Administration of supporting IT systems, code bases, databases
• Support teaching operations, in particular lab courses

Your profile:

• Strong interest in software development, machine learning, energy management, and technology in general
• Student of quantitative discipline like Compute Science, Engineering, Mathematics, Physics, or similar
• Experience in developing software using common IDEs and programming languages (e.g., Python) in a team
• Hardware affinity, ideally experience with electrical engineering lab work

Our offer:

We offer you the opportunity to support our research within a team of highly motivated researchers. The position is for 6 months at 8h/ week. Later extension is possible.

Your application:

We are looking forward to your application until October 26, 2026. Please submit it as one single PDF file via email to student-applications.emt@ed.tum.de. The application should contain the following documents:

• Cover letter presenting you qualifications and experiences
• Curriculum vitae
• Academic transcripts

Kontakt: student-applications.emt@ed.tum.de