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Portal > Offres > Offre UMR3589-MATPLU-001 - CDD post-doctoral (H/F) sur la calibration des prévisions d'ensemble météorologiques pour les énergies renouvelables

Postdoctoral position (H/F) for calibration of meteorological ensemble forecasts for renewable energy sources

This offer is available in the following languages:
Français - Anglais

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General information

Reference : UMR3589-MATPLU-001
Workplace : TOULOUSE
Date of publication : Tuesday, March 24, 2020
Type of Contract : FTC Scientist
Contract Period : 12 months
Expected date of employment : 1 September 2020
Proportion of work : Full time
Remuneration : 2600€ to 3700€ gross per month depending on the experience
Desired level of education : PhD
Experience required : 1 to 4 years

Missions

Within the framework of the European project H2020 EoCoE-II, the CNRM (CNRS/Météo-France) offers a 12-month (approx.) post-doctoral fixed-term contract. EoCoE-II (https://www.eocoe.eu/) is an energy-oriented centre of excellence funded by the European Union research programme. Within the framework of this program, the CNRM provides calibrated meteorological data of wind and radiation from ensemble forecasts. These data are then used to optimize the wind and solar power generation grid, respectively. The main objective of the work is to develop and improve methods for calibrating ensemble forecasts. The work is based on statistical tools and an existing work environment, which are the software used for the calibration of Météo-France forecasts.

Activities

More specifically, it will be about :
- develop and carry out the calibration of various wind and solar radiation forecasting sets,
- to evaluate, on independent data, the quality of the calibrated products, to test different options in the choice of learning sets,
- to develop new methods and evaluate their contribution, such as methods that calibrate forecasts according to whether or not they belong to particular meteorological structures (e.g. cloudy areas).

Skills

The incumbent of the post will need to have good analytical skills, autonomy and teamwork skills, as well as good writing skills. He/she must have a PhD thesis and a good level of English. Proficiency in computer languages for statistics (R or Python), as well as good knowledge and experience in statistical learning are required. Previous experience in handling large geophysical databases (model output and observations) would be appreciated.

Work Context

The post-doctoral student will be integrated into the CNRM team that develops and maintains Météo-France's statistical calibration software, and conducts research on statistical learning methods.

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