Autonomous Decision Support System Developer
5 days ago
About the Job
DTU Wind is seeking a highly skilled and motivated PhD student to work on the development and implementation of an autonomous decision support system for optimized maintenance in wind turbine infrastructure. The successful candidate will have a strong background in engineering or applied mathematics/computer science, with a keen interest in scientific programming, machine learning, and data science.
The PhD project aims to create a decision support system that utilizes machine learning and data analytics to predict and prevent faults in wind turbines. This involves collecting and analyzing large datasets, developing predictive models, and implementing autonomous decision-making algorithms.
About DTU Wind
DTU Wind is a leading research center at Danmarks Tekniske Universitet (DTU), dedicated to advancing knowledge and innovation in wind energy technology. Our team consists of experts from various disciplines, working together to tackle some of the most complex challenges facing the industry today.
We offer a unique opportunity to be part of IntelliWind, a Doctoral Network funded by the EU Marie Skłodowska-Curie Actions program. As a member of this network, you will benefit from collaboration with top researchers and engineers from academia and industry, as well as access to cutting-edge facilities and resources.
Responsibilities and Qualifications
- Collect and analyze large datasets to develop predictive models and identify key performance metrics.
- Implement machine learning algorithms and test their effectiveness in predicting and preventing faults in wind turbines.
- Collaborate with interdisciplinary teams to design and develop a decision support system that utilizes machine learning and data analytics.
Benefits and Opportunities
We offer a competitive salary and benefits package, including a generous allowance and opportunities for professional growth and development. You will also have the chance to collaborate with top researchers and engineers from academia and industry, as well as access to cutting-edge facilities and resources.
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