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Bayi Glacier in Qilian Mountain, China (Credit: Xiaoming Wang, distributed via imaggeo.egu.eu)

Job advertisement Postdoctoral Research Associate in short-term wind and solar power forecasting

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European Geosciences Union

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Postdoctoral Research Associate in short-term wind and solar power forecasting

Position
Postdoctoral Research Associate in short-term wind and solar power forecasting

Employer
Ecole Polytechnique Federal de Lausanne (EPFL) logo

Ecole Polytechnique Federal de Lausanne (EPFL)

Homepage: https://www.epfl.ch/labs/wire/


Location
Lausanne, Switzerland

Sector
Academic

Relevant divisions
Atmospheric Sciences (AS)
Energy, Resources and the Environment (ERE)
Nonlinear Processes in Geosciences (NP)

Type
Full time

Level
Entry level

Salary
min. 86000 € / Year

Required education
PhD

Application deadline
Open until the position is filled

Posted
9 March 2023

Job description

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 between 6h up to a few days) 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 machine learning (ML) tools for wind
and solar energy production. The research framework will involve data from 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., deep learning, stochastic optimization,
etc.).
The position will be developed 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.

Requirements

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 Matlab and Python (desirable).
·Excellent English writing and speaking skills.
·Strong peer-reviewed journal publication record.

Position conditions
Full time (100%) contract renewable every year up to three years. Salaries in Switzerland are highly
competitive internationally.
Starting date: May-June 2023


How to apply

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 [fernando.porte-agel@epfl.ch].