PhD scholarship in Reinforcement Learning based Wind Farm Control Optimisation – DTU Wind

2 months ago

Kongens Lyngby, Denmark Danmarks Tekniske Universitet (DTU) Full time

PhD scholarship at DTU Wind in Reinforcement Learning-based Wind Farm Control Optimization in IntelliWind Marie-Curie network.

Perfect for those passionate about low carbon energy and climate change solutions. Requires experience in programming and machine learning. Join us to innovate in renewable energy

If you are aspiring for a career in industrial R&D or academia, with a passion for the production of low carbon energy, particularly wind energy and its most intriguing research challenges, then this subject may be of interest to you.

We are seeking a passionate, curious, and enthusiastic new team member committed to addressing climate change by advancing renewable energy systems. We are looking for someone who thrives on solving complex problems, isn't afraid to ask challenging questions, and possesses the determination to pursue innovative solutions in a rapidly evolving field.

DTU Wind invites applications for a position as a PhD student in Wind Farm Control (WFC) Optimization, focusing on Reinforcement Learning (RL) techniques, as part of Design and impact assessment of autonomous actions investigated in IntelliWind.

In this role, you will have the chance to evolve within academia at DTU Wind, located in Risø, near Roskilde, just 30 minutes from Copenhagen. You will benefit from advanced training in various European universities and industry, participate in scientific discussions within the rich context of the Marie Skłodowska-Curie Action Doctoral Network (MSCA DN) "Intelligent systems for autonomous Wind power plant operations" (IntelliWind).

You are a committed individual with a strong background in engineering or computer science, with a keen interest in scientific programming and machine learning. Your curiosity drives you to explore and understand the intricacies of wind energy systems, and your self-motivation pushes you to expand the boundaries of what is currently possible for a better tomorrow.

If you also work efficiently in a project team and take responsibility for your own research goals you will be a good fit in our team. There are additional criteria for Marie Skłodowska-Curie DNs, that requires that you have:

  • Not been awarded a title of PhD (Applicants who have successfully defended their doctoral thesis but not yet formally been awarded the doctoral degree will not be considered eligible.)
  • Not resided or carried out your main activity in Denmark, for more than 12 months within the last 3 years.

Your primary tasks will be to:

  • Develop and test new AI-driven algorithms for WFC, emphasizing accuracy, reliability, and robustness.
  • Include impact assessment to estimate the potential benefits of the AI-driven WFC strategies compared to physics-based approaches.
  • Assess the risk and uncertainties through uncertainty assessment involving, for example, ensemble modeling.

The present project will take advantage of collaboration with researchers and engineers at DTU and at external partners in academia as well as the industry.

We offer you the opportunity to be a part of IntelliWind, which will not only facilitate sixteen DCs in reaching a high level of technical and project-specific excellence but will also provide you with many opportunities for developing skills that are transferable to a broader landscape of opportunities. You will have the opportunity to visit industry and other academic institutions within the consortium. After completing the program, you will have a thorough understanding of the process from research via innovation to industry implementation and a strong career-defining network.

The IntelliWind Doctoral Network provides training for a new creative, entrepreneurial, innovative, and resilient industry-oriented academic generation ready to face current and future challenges towards reducing the role of humans in the decision process and the need for direct human interventions in the operations and maintenance process. The trained Doctoral Candidates will be able to convert knowledge and ideas into new products, and services for economic and social benefit.

You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree. In addition, we expect that you have some level of:

  • Experience programming with scientific python
  • Experience with data science/analytics and machine learning methods
  • Experience with wind energy topics

Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education.

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union.

The period of employment is 3 years. Starting date is 1 December 2024 (or according to mutual agreement). The position is a full-time position.

Application procedure
Your complete online application must be submitted no later than 15 September 2024 (23:59 Danish time) . 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

You may apply prior to obtaining your master's degree but cannot begin before having received it.

Applications received after the deadline will not be considered.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

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