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Thesis Research Position in Renewable Energy Solutions
vor 3 Wochen
The transition towards renewable energy sources presents unique challenges in the development of autonomous energy systems that operate independently from a central power grid. It is essential to account for extreme scenarios to ensure that energy demand is consistently met. Our team has devised a robust optimization strategy to tackle these extreme scenarios during the energy system optimization process. However, this results in a complex multi-level optimization challenge that can be computationally intensive.
- Your responsibilities for this thesis will include the implementation of machine learning surrogate models to streamline one of the optimization levels, enhancing computational efficiency.
- You will engage in the development of various machine learning models, such as neural networks and support vector machines, to derive optimal solutions for optimization challenges.
- Subsequently, you will evaluate these models across different optimization scenarios related to energy systems, which may include linear, mixed-integer linear, and non-linear problems.
- Currently enrolled in a master’s program in engineering, computer science, simulation science, data science, or a related discipline.
- Proficient programming skills in Python.
- Experience with a prominent deep learning framework, preferably PyTorch, is advantageous.
- Fluency in English or German, both spoken and written.
- Ability to work independently with strong analytical capabilities.
- Openness to learning new methodologies.
We are engaged in addressing contemporary issues that significantly affect society, and we invite you to contribute to this transformative work. We provide you with:
- A clearly defined research topic with specific objectives, facilitating a prompt start.
- Interdisciplinary collaboration that integrates physics, mathematics, computer science, and engineering.
- Comprehensive guidance from experienced colleagues.
- Access to exceptional scientific and technical resources.
- Top-notch technical equipment to support effective remote work.
- A spacious research environment with green areas, fostering networking opportunities and promoting physical activities alongside your professional endeavors.
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