Description:
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2 PhD and 2 Postdoc
positions in Machine Learning for Geosciences [ERC Consolidator Grant
project]
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We are searching for
outstanding candidates with a strong interest in machine learning and
geosciences to cover 2 PhD and 2 postdoctoral positions to join the
Image and Signal Processing (ISP) group in the Universitat de
Valencia, Spain, http://isp.uv.es. 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
http://isp.uv.es/sedal.pdf
*** 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/PhD 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.
Positions will cover two different profiles: (1) Expertise in 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) Expertise in 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.
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Application Instructions:
*** Application
details
- How? Send me:
2-pages CV, motivation letter, 3 best papers, 3 recommendation
letters or contacts
Send your dossier
in one single PDF to gustau.camps@uv.es, subject: SEDAL application
- When? Preferred
starting dates: January or 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
- Informal inquiries
may be addressed to Prof. Dr. Gustau Camps-Valls, gustau.camps@uv.es
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