Dear all,

Please find attached a job offer at Cesbio. I would appreciate if you
could forward it to interested candidates. They can apply online here:

[https://cnes.fr/en/les-ressources-humaines-du-cnes/satellite-remote-sensing-engineer-mf-ref-2016-dct-002]

Best regards,

J. Inglada

           ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
            18-MONTH POSITION AT CNES/CESBIO, TOULOUSE, FRANCE -
             IMPLEMENTATION OF A HIGH PERFORMANCE COMPUTING
            LAND-COVER MAP PRODUCTION SYSTEM USING SENTINEL
                           IMAGE TIME SERIES
           ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

1 Background
════════════

  CESBIO is developing the `iota2' operational processing chain for the
  production of land cover maps using image time series. The main data
  source for this processing chain will be Sentinel-2, but Sentinel-1
  and VHR images (SPOT6/7, Pléiades) will also be exploited.

  This project contributes to the Scientific Expertise Centre on Land
  Cover of the Theia Land Data Centre [1].

  `iota2' is a free and open source software [2] based on the Orfeo
  Toolbox library [3] and it runs on standard work stations and HPC
  clusters.

  The processing chain is able to produce large-scale land cover maps
  (see [4] and [5]).

  CNES is opening a 18-month position at CESBIO to work on the
  development, maintenance and validation of the `iota2' processing
  chain.

2 Work description
══════════════════

  The selected candidate will:
  • work on the maintenance and evolution of the `iota2' processing
    chain by implementing algorithms and work-flows in C++ using the
    Orfeo Toolbox;
  • prototype and validate feature extraction and machine learning
    algorithms on CNES' HPC infrastructure leveraging the MPI library;
  • participate in the development of the infrastructure for the
    distribution of land cover maps to end users.

  The candidate should have a solid engineering education with majors in
  signal processing, image processing or computer science. Strong
  foundations in software development in C++ and Python on GNU/Linux for
  science applications, machine learning and data analysis. Knowledge of
  the geo-spatial domain tools (GIS, WMS, OpenLayers) will be
  appreciated.


3 Contact
═════════

  Apply online: 
https://cnes.fr/en/les-ressources-humaines-du-cnes/satellite-remote-sensing-engineer-mf-ref-2016-dct-002

Footnotes
─────────

[1] [http://www.theia-land.fr/node/557]

[2] [http://tully.ups-tlse.fr/jordi/iota2]

[3] [https://www.orfeo-toolbox.org/]

[4] [http://www.cesbio.ups-tlse.fr/multitemp/?p=6382]

[5]
[http://www.cesbio.ups-tlse.fr/multitemp/wp-content/uploads/2016/02/SudOuestMosaic_France2014_V1_ColorIndexedT.html]

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