Postdoc position within Wind Turbine Predictive Health Monitoring
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Odense M
The section of Applied AI and Data Science at the Maersk Mc-Kinney Moller Institute, Faculty of Engineering, University of Southern Denmark, invites applications for one or more vacant postdoctoral position(s) in data science with focus on wind turbine predictive health monitoring for a period of 2 years. The starting date in 2022 will be agreed with the successful candidate.
Profile and requirements
Within the field of Data Science and Machine Learning, we seek applications from candidates with expertise in one or more of the following backgrounds:
Experience in working with wind turbine data is a plus but not a necessity. A suitable candidate is expected to highlight skills in machine learning, including subspace methods for feature selection and analysis of time-series data.
The successful candidate will take part in shaping data driven diagnostic solutions for our industry partner (Siemens Gamesa Renewable Energy (SGRE)) by being responsible for the development and implementation of diagnostic models based on heterogeneous data sources. The applicant is expected to conduct site visits at SGRE and work tightly with knowledgeable engineers in the wind industry sector.
The project SGRE produces, sells, and services wind turbines, with the latter producing a large amount of data to be monitored. However, components such as blade bearings are not equipped with sensors and can therefore only be monitored indirectly. The aim of the project is to identify proxy features for the blade bearing and incorporate them into diagnostic and predictive models. The data used in this project originates from both operational wind turbines (SCADA, fastlog, events etc.), and simulations (physical models, system control, etc.).
Contact information
Further information regarding the project can be obtained from Associate Professor Jürgen Herp, phone: +45 65509232, e-mail: [email protected].
If you experience technical problems you must contact [email protected].
Conditions of employment
Employment as a postdoc requires scientific qualifications at PhD level. Employment as a postdoc is temporary and will cease without further notice at the end of the period.
Research will be predominant in the position. Teaching assignments can be agreed individually. Furthermore, other types of assignments may occur to a limited degree. The Faculty determines the distribution of the various assignments. The weighting of the different assignments may vary over time. The successful applicant will be employed in accordance with the agreement between the Ministry of Finance and the Danish Confederation of Professional Associations. Please check links for more information on salary and taxation.
The assessment process
Read about the Assessment and selection process. Shortlisting may be used.
Application procedure
The faculty expects applicants to read How to apply before applying.
The application must be in English and must include:
- Motivated application.
- Detailed Curriculum Vitae.
- Certificates/Diplomas (MSc and PhD).
- List of publications indicating the publications attached.
- Examples of the most relevant publications. Please attach one pdf-file for each publication.
- Reference letters and other relevant qualifications may also be included.
The application deadline is 17.03.2022.
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
Further information for international applicants about entering and working in Denmark.
Further information about The Faculty of Engineering.
Profile and requirements
Within the field of Data Science and Machine Learning, we seek applications from candidates with expertise in one or more of the following backgrounds:
- Physics,
- Mathematics,
- Engineering (with emphasis on data-driven modeling),
- Big Data Analytics,
- or similar.
Experience in working with wind turbine data is a plus but not a necessity. A suitable candidate is expected to highlight skills in machine learning, including subspace methods for feature selection and analysis of time-series data.
The successful candidate will take part in shaping data driven diagnostic solutions for our industry partner (Siemens Gamesa Renewable Energy (SGRE)) by being responsible for the development and implementation of diagnostic models based on heterogeneous data sources. The applicant is expected to conduct site visits at SGRE and work tightly with knowledgeable engineers in the wind industry sector.
The project SGRE produces, sells, and services wind turbines, with the latter producing a large amount of data to be monitored. However, components such as blade bearings are not equipped with sensors and can therefore only be monitored indirectly. The aim of the project is to identify proxy features for the blade bearing and incorporate them into diagnostic and predictive models. The data used in this project originates from both operational wind turbines (SCADA, fastlog, events etc.), and simulations (physical models, system control, etc.).
Contact information
Further information regarding the project can be obtained from Associate Professor Jürgen Herp, phone: +45 65509232, e-mail: [email protected].
If you experience technical problems you must contact [email protected].
Conditions of employment
Employment as a postdoc requires scientific qualifications at PhD level. Employment as a postdoc is temporary and will cease without further notice at the end of the period.
Research will be predominant in the position. Teaching assignments can be agreed individually. Furthermore, other types of assignments may occur to a limited degree. The Faculty determines the distribution of the various assignments. The weighting of the different assignments may vary over time. The successful applicant will be employed in accordance with the agreement between the Ministry of Finance and the Danish Confederation of Professional Associations. Please check links for more information on salary and taxation.
The assessment process
Read about the Assessment and selection process. Shortlisting may be used.
Application procedure
The faculty expects applicants to read How to apply before applying.
The application must be in English and must include:
- Motivated application.
- Detailed Curriculum Vitae.
- Certificates/Diplomas (MSc and PhD).
- List of publications indicating the publications attached.
- Examples of the most relevant publications. Please attach one pdf-file for each publication.
- Reference letters and other relevant qualifications may also be included.
The application deadline is 17.03.2022.
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
Further information for international applicants about entering and working in Denmark.
Further information about The Faculty of Engineering.
Information og data
Denne ledige stilling har jobtypen "Forsker", og befinder sig i kategorien "Sundhed og forskning".
Arbejdsstedet er beliggende i Odense M.
Jobbet er oprettet på vores service den 4.2.2022, men kan have været deaktiveret og genaktiveret igen.
Dagligt opdateret: Dette job opdateres dagligt ud fra jobudbyderens hjemmeside via vores søgemaskineteknologi og er aktivt lige nu.
- Forsker
- Odense M
- Torsdag den 17. marts 2022
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