The Wind Engineering and Renewable Energy (WiRE) Laboratory of the École polytechnique fédérale de Lausanne (EPFL) is looking to fill a Post-doc position in short-term wind and solar power forecasting models (typically from 6h to a few days). The successful Post-doc candidate will work in the development of hybrid – numerical weather prediction (NWP) and machine learning (ML) – forecasting models for wind and solar energy production, and their application to the largest Swiss wind and solar power plants. By using long time series of both wind or 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 ML-based tools (e.g., MLP, LSTM NNs, SVM, stochastic optimization, etc.).
The position is within the recently 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.
In addition to the research tasks related to the position, the candidate will contribute to teaching.
Interested candidates should send a single PDF file including: CV, a brief research statement and the contact details of 3 reference persons to: Prof. Fernando Porté-Agel [email@example.com].
In order to qualify for the position, the candidates are required to have:
·A completed a PhD degree.
·Proven knowledge of advanced machine-learning tools, large data-sets analysis, statistical (probabilistic) forecasting, uncertainty analysis, etc.
·Knowledge of energy systems modelling, especially within wind and solar power.
·Excellent computer programming skills in Python & Matlab.
·Excellent English writing and speaking skills.
·Strong peer-reviewed journal publication record.
- Level Excellent
Research fieldEngineeringEngineering » Simulation engineeringEnvironmental scienceEnvironmental science » Other
25th December 2023
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