PhD Researcher in AI-Driven Wind Farm Optimization

4 weeks ago


Kongens Lyngby, Lyngby-Tårbæk Kommune, Denmark Danmarks Tekniske Universitet (DTU) Full time
Join a Leading Research Team at DTU Wind

We are seeking a highly motivated PhD researcher to join our team at DTU Wind, focusing on AI-driven wind farm optimization. As a PhD candidate, you will contribute to the development of innovative solutions for next-generation wind farm design methodology.

Our team is part of the TWEED Doctoral Network, a prestigious program funded by the EU's Horizon Europe MSCA program. You will have the opportunity to work closely with experts from academia and industry, exploring the potential of AI in engineering design.

Key responsibilities include:

  • Developing a framework/methodology to integrate AI into wind farm design optimization
  • Investigating the potential of combining machine learning-based surrogate modeling with AI-enabled search and evolutionary algorithms
  • Contributing to the development of TopFarm/TopDesign, an open-source wind farm optimization tool

As a PhD candidate, you will be part of a dynamic team at DTU Wind, working on cutting-edge research projects. You will have the opportunity to collaborate with international experts, attend conferences, and publish your research in top-tier journals.

Requirements:

  • Master's degree in engineering or computer science
  • Proficiency in scientific programming (preferably with Python)
  • Background in optimization

Desirable additional background knowledge:

  • Wind energy
  • Wind farm flow physics (wind farm wake)
  • AI and machine learning

DTU Wind offers a stimulating research environment, with access to state-of-the-art facilities and collaboration opportunities with industry partners. We are committed to academic excellence and provide a competitive salary and benefits package.

Apply now to join our team and contribute to the development of innovative solutions for wind energy digitalization.



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