EDUCATION

• You hold a PhD degree in remote sensing, image or signal processing, machine learning, applied mathematics, computer engineering, telecommunications engineering, or computer sciences (or a similar field).

EXPERIENCE AND SKILLS

• Good knowledge of EO toolkits (e.g., GDAL, SNAP, EnMAP box, etc.).
• Excellent programming skills (e.g., Python, C/C++, Matlab, IDL, etc.).
• Advanced knowledge of different Deep Learning and Machine Learning algorithms for supervised, unsupervised, and semi-supervised learning.
• Experience in applying Deep Learning and Machine Learning algorithms to different data sets and in particular Earth Observation data for classification, image segmentation, and geophysical parameters retrieval (e.g., Sentinel-1 and -2, Worldview, TerraSAR-X, COSMO-SkyMed, etc.).
• Hands-on experience with at least one of the following popular Machine Learning/Deep Learning frameworks: Scikit-learn, Tensorflow, Pytorch, and Keras.
• Knowledge of advanced statistical methods to evaluate Machine Learning models.
• Experience with distributed cloud storage systems and cloud computing services.
• Experience in HPC (including heterogeneous architectures).
• Experience with image processing software.
• Excellent skills in presenting scientific research, writing papers in scientific journals, and crafting technical reports.
• Communicative and willing to learn, self-organized, and creative.
• Ability to work both independently and collaboratively in an international team.

LANGUAGE SKILLS

• Fluency in English, both oral and written. Other relevant languages are an asset.

Please refer the Job description for details