Annonce en lien avec l’Action/le Réseau : aucun
Laboratoire/Entreprise : ICube/SERTIT, University of Strasbourg
Durée : 6 months
Contact : iadb@icube.unistra.fr
Date limite de publication : 2020/2/1
Contexte :
Created in 2013, the laboratory brings together researchers from the University of Strasbourg, the CNRS (French National Center for Scientific Research), the ENGEES and INSA of Strasbourg in the fields of engineering and computer science, with imaging as the unifying theme.
With around 650 members, ICube is a major driving force for research in Strasbourg whose main areas of application are biomedical engineering and sustainable development.
SERTIT, a service platform of ICube, known for its ISO certified rapid mapping service, is seeking to accelerate its mapping activities through artificial intelligence. This service assists in post-crisis emergency management (e.g. ground rescue, reconstruction efforts …).
You will join a transversal team of researchers, software engineers and geomatics specialists from SERTIT (Regional service for remote sensing and image processing), SDC (Data science and knowledge), IMAGeS (Images, learning, geometry and statistics), working on automatic feature extraction from satellite imagery.
http://icube.unistra.fr/en/
Sujet :
● Users need to map buildings during rapid mapping after a disaster strikes
● Collaborate with research teams to transfer techniques from medical imaging
to remote sensing
● Develop new innovative and enhance existing solutions to automatically
extract building footprints using:
o Deep Learning
o Object based segmentation algorithms
Profil du candidat :
Undergraduate student of a computer science/geomatics degree or similar.
Formation et compétences requises :
Must have:
● Experience with the Python scientific computing ecosystem (Pandas, numpy, scikit-learn, scikit-image, etc.)
● Knowledge of Machine Learning workflows and techniques (e.g. best practices around training data management, understand basics of numerical optimization)
● Familiarity with Linux environments
● Have excellent communication skills and a strong team player
● Good knowledge of English, French is not mandatory
● Can-do attitude!
Nice to have or interested in learning:
● Experience with GIS software and packages like ArcGIS, QGIS, GDAL or PostGIS
● Experience with a deep learning framework (Tensorflow, PyTorch, Caffe, Theano, Keras)
● Experience with remote sensing and/or geographic raster/vector data
Adresse d’emploi :
300 Bd Sébastien Brant
67412 Illkirch
Document attaché : Stage_2020_Offre_EN_-_final.pdf