Research Assistant in Machine Learning: The University of Applied Sciences Weihenstephan-Triesdorf is offering an exciting opportunity for a Research Assistant position focused on developing machine learning and optimisation algorithms for large-scale battery storage systems within the energy sector. This temporary position supports innovative research aimed at enhancing grid efficiency and cost-effectiveness.
Research Assistant (M/F/D) in Machine Learning and Optimisation for Energy Applications
Designation
Research Assistant (M/F/D)
Research Area
- Machine Learning
- Optimisation
- Energy Systems
- Battery Storage
Location
Campus Weihenstephan, Germany
Eligibility/Qualification
- A completed scientific university degree (Diploma [Univ.] or Master’s degree) in one of the following fields:
- Energy Economics
- Electrical Engineering
- Energy Management
- Energy Technology
- Environmental Engineering
- Computer Science
- Mathematics
- Physics
- Statistics
- Artificial Intelligence
- Data Science
- Mechatronics
- Experience and interest in energy economics, machine learning, or optimisation.
- Good programming skills (preferably in Python) and experience with machine learning frameworks (e.g., sklearn, PyTorch) is advantageous.
- Strong scientific curiosity, teamwork skills, and independent working style.
- Fluency in written and spoken English; German language skills are a plus.
Job Description
- Conduct research on battery storage systems and their integration into the energy system.
- Develop innovative optimisation and machine learning-based methods to address challenges faced by grid and storage operators.
- Collaborate with experts in machine learning, optimisation, and energy transition.
- Write scientific publications and present findings at conferences.
- Play a role in shaping a new field of research.
- Opportunity for pursuing a doctorate is explicitly supported.
How to Apply
Interested candidates should submit their application via the university’s online form. The application should include:
- A cover letter
- A CV in tabular form
- Proof of required education
- Work references
Please apply exclusively via the “APPLY NOW” button on the university’s website.
Last Date for Apply
July 20, 2025
For further queries regarding the application process, please contact Bianca-Maria Unterholzner at bianca-maria.unterholzner@hswt.de or call +49 8161 71-3862. For technical questions, reach out to the respective professors mentioned in the job listing.
