Postdoctoral Researcher on Short-Term Wind and Solar Power Forecasting
École polytechnique fédérale de Lausanne, EPFL
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EPFL, the Swiss Federal Institute of Technology in Lausanne, is one of the most dynamic university campuses in Europe
and ranks among the top 20 universities worldwide. The EPFL employs more than 6,500 people supporting the three main
missions of the institutions: education, research and innovation. The EPFL campus offers an exceptional working
environment at the heart of a community of more than 18,500 people, including over 14,000 students and 4,000
researchers from more than 120 different countries.
Postdoctoral Researcher on Short-Term Wind and Solar Power Forecasting
Main duties and responsibilities
The Wind Engineering and Renewable Energy (WiRE) Laboratory at the École polytechnique fédérale de Lausanne (EPFL) is
looking to fill a post-doctoral position in the field of short-term (typically from 6h to 24h) power forecasting of
renewable energy sources (wind and solar). The successful post-doc candidate will work in the development of hybrid
forecasting models combining numerical weather prediction (NWP) models with artificial intelligence (AI) techniques for
wind and solar energy production.
Mission
The research framework will involve data collected from various wind and solar power plants in Switzerland and
worldwide. By using long time series of wind/solar power production, as well as NWP outputs (big data), the candidate
will focus on the development and testing of new forecasting models, with especial emphasis in novel AI-based methods
(e.g., deep learning, explainable and physics-informed AI, large language models, etc.).
The position will be developed within the funded project entitled “UrbanTwin: An urban digital twin for climate
action: Assessing policies and solutions for energy, water and infrastructure”, as part of the ETH-Joint Initiative
funding program.
Profile
In order to qualify for the position, the candidates are required to have:
- A completed PhD degree.
- Experience in machine-learning methods.
- Some skill in at least one of these topics :
- Large data sets analysis
- Statistics and uncertainty analysis (probabilistic)
- Weather modelling (Numerical Weather Prediction)
- Computing experience with Python.
- Excellent English writing and speaking skills.
- Strong peer-reviewed journal publication record.
We offer
- A stimulating and international working environment in the EPFL campus/Lausanne.
- Competitive salary and excellent working conditions.
- Opportunity to perform state-of-the-art research in one of the most dynamic scientific institutions in Europe.
Informations
Contract Start Date : as soon as possible
Activity Rate : 100%
Contract Type: CDD
Duration: one year with possibility of renewal
Reference: Please send a single PDF file including CV, a brief research statement and the contact details of 3
reference persons
For any further information, please contact Prof. Porté-Agel at fernando.porte-agel@epfl.ch
and ranks among the top 20 universities worldwide. The EPFL employs more than 6,500 people supporting the three main
missions of the institutions: education, research and innovation. The EPFL campus offers an exceptional working
environment at the heart of a community of more than 18,500 people, including over 14,000 students and 4,000
researchers from more than 120 different countries.
Postdoctoral Researcher on Short-Term Wind and Solar Power Forecasting
Main duties and responsibilities
The Wind Engineering and Renewable Energy (WiRE) Laboratory at the École polytechnique fédérale de Lausanne (EPFL) is
looking to fill a post-doctoral position in the field of short-term (typically from 6h to 24h) power forecasting of
renewable energy sources (wind and solar). The successful post-doc candidate will work in the development of hybrid
forecasting models combining numerical weather prediction (NWP) models with artificial intelligence (AI) techniques for
wind and solar energy production.
Mission
The research framework will involve data collected from various wind and solar power plants in Switzerland and
worldwide. By using long time series of wind/solar power production, as well as NWP outputs (big data), the candidate
will focus on the development and testing of new forecasting models, with especial emphasis in novel AI-based methods
(e.g., deep learning, explainable and physics-informed AI, large language models, etc.).
The position will be developed within the funded project entitled “UrbanTwin: An urban digital twin for climate
action: Assessing policies and solutions for energy, water and infrastructure”, as part of the ETH-Joint Initiative
funding program.
Profile
In order to qualify for the position, the candidates are required to have:
- A completed PhD degree.
- Experience in machine-learning methods.
- Some skill in at least one of these topics :
- Large data sets analysis
- Statistics and uncertainty analysis (probabilistic)
- Weather modelling (Numerical Weather Prediction)
- Computing experience with Python.
- Excellent English writing and speaking skills.
- Strong peer-reviewed journal publication record.
We offer
- A stimulating and international working environment in the EPFL campus/Lausanne.
- Competitive salary and excellent working conditions.
- Opportunity to perform state-of-the-art research in one of the most dynamic scientific institutions in Europe.
Informations
Contract Start Date : as soon as possible
Activity Rate : 100%
Contract Type: CDD
Duration: one year with possibility of renewal
Reference: Please send a single PDF file including CV, a brief research statement and the contact details of 3
reference persons
For any further information, please contact Prof. Porté-Agel at fernando.porte-agel@epfl.ch