Thesis Research Position in Renewable Energy Solutions

vor 3 Wochen


Jülich, Nordrhein-Westfalen, Deutschland Forschungszentrum Jülich Vollzeit
Position Overview:

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.
Candidate Profile:
  • 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.
What We Offer:

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.
In addition to engaging tasks and a supportive work atmosphere, we offer a wealth of additional benefits.

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