January 2016
Message 73

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[Met-jobs] 2 PhD positions in Machine Learning for Geosciences [ERC Consolidator Grant project]

From Gustau Camps-Valls <>
To Gustau Camps-Valls <>
Date Sun, 24 Jan 2016 20:50:48 +0100

Dear Colleagues,

I'd appreciate if you could circulate these two PhD positions in my group attached to an ERC Consolidator Grant project. Two different profiles: computer science and geosciences.

Thanks so much!

Best regards,


ERC project: 2 PhD positions in Machine Learning for Geosciences

We are searching for outstanding candidates with a strong interest in machine learning for geosciences to cover 2 PhD positions to join the Image and Signal Processing (ISP) group in the Universitat de Valencia, Spain, The positions are funded by an ERC Consolidator Grant 2015-2020 entitled "Statistical Learning for Earth Observation Data Analysis" (SEDAL) under the direction of Prof. Gustau Camps-Valls. More info about the openings in and

*** 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 students 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 climate science, remote sensing, and geoscience problems. Positions will cover two different profiles:

(1) Remote sensing and geosciences: model inversion, radiative transfer models, biogeochemistry, climate science, detection and attribution, global carbon/heat/water fluxes, in-situ datasets for land/vegetation/atmosphere monitoring; and

(2) Machine learning, statistics and signal processing: regression and time series analysis, change and anomaly detection, structured/relational/transfer learning, graphical models and causal inference. In both cases, 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.

*** Application details

- How? Send me: 2-pages CV, motivation letter, 3 best papers, 3 recommendation 
letters or contacts
- When? Preferred starting dates: May 2016
- How long? 1 year contract (extendable upon mutual satisfaction and 
qualifications to 3-4 years)
- How much? Salary according to UV scales including social security, health 
insurance benefits, and travel money
- Where? Valencia, Spain, Mediterranean, nice weather, hike and beach. 
Excellent cost-of-living index = 55

*** Contact

* Important notice before applying: read the project info above carefully, read (some of) the related papers, and think about the motivation and goals of the project. And now, sit back, breath and think: could you contribute into something? Do you really understand what we want to do in SEDAL? Do you have ideas to share with me? Do you have the right background and expertise? Are you brilliant to undertake the challenge?

* Ready to apply? Send your dossier in one single PDF to, 
subject: SEDAL application

Prof. Gustau Camps-Valls
Image and Signal Processing Group (ISP)
Image Processing Laboratory (IPL)
Office: 3.2.4
Parc Científic - Campus de Paterna
Universitat de València
C/ Catedrático José Beltrán, 2
46980 Paterna, València. Spain.
Tlf: +34 963 544 064
Fax: +34 963 543 261

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