Data Scientist for Renewable Energy System Development

1 day ago


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

Our PhD project focuses on creating a cutting-edge, modular, autonomous decision support system to optimise the maintenance of wind turbines.

We are seeking an ambitious, skilled data scientist with expertise in machine learning and data analysis to contribute to this project. Your primary tasks will include developing tools to automatically analyse sensor data, identifying signals or metrics that indicate asset health, and collaborating with researchers and engineers at DTU and external partners.

This role offers opportunities to advance your knowledge in scientific programming, data science, and machine learning while addressing climate change by enhancing renewable energy systems. You will work closely with our team to conceptualise and realise a versatile DSS tailored to improve the O&M practices of wind turbines.

The successful candidate will have a strong background in engineering or applied mathematics/computer science, excellent programming skills, and experience with data science/analytics and machine learning methods. They should be able to efficiently work in a project team and take responsibility for their own research goals.

You will have the opportunity to participate in a Doctoral Network funded by the EU Marie Skłodowska-Curie Actions program (MSCA DN), which will provide you with advanced training in European universities and industry, as well as the chance to collaborate with Vestas and the University of Granada.

In this position, you will evolve within academia at DTU Wind, located near Roskilde, Denmark. You will benefit from close collaboration with researchers and engineers at DTU and external partners, and participate in scientific discussions within the rich context of the Marie Skłodowska-Curie Action Doctoral Networks.

About the Project:

  • Conceptualisation and realisation of a versatile, modular, autonomous decision support system (DSS) tailored to enhance the O&M practices of wind turbines.
  • Identify signals or metrics that can be indicators of the asset health state related to the fault/degradation modes being studied.
  • Develop tools to automatically analyse sensor data to evaluate relevant metrics and relate them to other external factors.

Qualifications and Responsibilities:

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

About DTU Wind:

DTU Wind is part of the Technical University of Denmark (DTU), a leading technical university in Europe. Our mission is to develop innovative solutions to address global challenges, particularly in the field of renewable energy. We offer a unique opportunity to contribute to groundbreaking research and development projects, working closely with industry partners and international colleagues.



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