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Annonce

13 mars 2017

PhD student position in Machine Learning for Geosciences [ERC project]


Catégorie : Doctorant


We are searching for an outstanding candidate with a strong interest in machine learning and geosciences to cover one PhD student position to join the Image and Signal Processing (ISP) group in the Universitat de Valencia, Spain, http://isp.uv.es. The position is fully funded by an ERC Consolidator Grant 2015-2020 entitled "Statistical Learning for Earth Observation Data Analysis" (SEDAL), http://isp.uv.es/sedal.html, under the direction of Prof. Gustau Camps-Valls.

 

The project and job description

We aim to develop the next generation of statistical inference methods to analyze Earth Observation (EO) data. Machine learning models have helped to monitor land, oceans, and atmosphere through the analysis and estimation of climate and biophysical parameters. Current approaches, however, cannot deal efficiently with the particular characteristics of remote sensing data. We will develop advanced regression (retrieval, model inversion) methods to improve efficiency, prediction accuracy and uncertainties, encode physical knowledge about the problem, attain self-explanatory models, learn graphical causal models to explain the complex interactions between essential climate variables and observations, and discover hidden essential drivers and confounding factors in Climate/Geo Sciences.

Highly motivated researchers with a degree in computer science, statistics, machine learning, electrical engineering, physics, or mathematics are encouraged to apply. All candidates should have a solid understanding and knowledge of machine learning and statistics, and being particularly interested in remote sensing and geoscience problems. The thesis will address problems in regression, graphical models and causal inference. Good programming skills (Matlab/Python/R/C++), a critical and organized sense for data analysis, as well as maturity and commitment, strong communication, presentation and writing skills are a big plus.

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