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PhD Researcher in AI-Driven Wind Farm Optimization
1 month ago
We are seeking a highly motivated and talented PhD researcher to join our team at DTU Wind, a leading research institution in wind energy. As a PhD researcher, you will be part of a dynamic and interdisciplinary team working on the development of AI-driven wind farm optimization methods.
About the Project
The project focuses on the development of a framework/methodology to better integrate AI into the workflow of wind farm design optimization. You will investigate the potential of combining the strengths of Machine Learning based surrogate modelling for wind farm performance and loading with AI enabled search & evolutionary algorithms. Your research will contribute to the development of TopFarm/TopDesign, the open source wind farm optimization tool developed in DTU Wind.
Responsibilities and Qualifications
- Develop a framework/methodology to integrate AI into wind farm design optimization
- Investigate the potential of combining Machine Learning based surrogate modelling with AI enabled search & evolutionary algorithms
- Contribute to the development of TopFarm/TopDesign, the open source wind farm optimization tool
Requirements and Qualifications
- Master's degree in an engineering field or computer science
- Proficiency in scientific programming (preferably with Python)
- Background in optimization
What We Offer
- A dynamic and interdisciplinary research environment
- The opportunity to work on a cutting-edge project in wind energy digitalization
- A PhD scholarship with a competitive salary and benefits
How to Apply
Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:
- A letter motivating the application (cover letter)
- Curriculum vitae
- Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale
Application Deadline
The application deadline is 15 October 2024. Applications received after the deadline will not be considered.
