The company
adwäisEO S.A. is a fast-growing company, leader in the sector of it services related to the Space Ground Segment. Its clients are Space Agencies (i.e. ESA and Luxembourg Space Agency), public space organization (i.e. Mercator, Copernicus) and private companies. Among our projects: the biggest collaborative ground segment of Europe (www.collgs.lu) and the Data Archival, Management and Processing Services (DAMPS) for ESA (www.damps.info ) that covers together the 80 % of ESA EO data, the systematic production of Sentinel-3A data and the reprocessing of Sentinel 2, so far the biggest reprocessing of the history. Thanks to cutting-edge expertise in Remote Sensing, Data Analytics and ICT, the company offers algorithms and processes for Big Data Mining and Data Transformations along with high performing and cost-effective solutions such as multi-Petabytes archives, intuitive geoportals, and efficient processing solutions in cloud and/or HPC environment. The company owns a massive capacity of storage and computing in its own premises in HPC and/or cloud environment.
The position
adwäisEO SA is looking for a talented EO Data Engineer to join its data team. The scientist will work on the generation of added value products from EO data. The activities will include a contribution to the HERITAGE project recently founded by Lux Innovation in the Joint Call HPC. The project focuses on the creation of a crop forecast model based on Machine Learning. She/he will be contributing to:
- Definition of data and ML models to turn EO data into information.
- Definition of processing chain including preprocessing of EO data and postprocessing of model output.
- Definition of data requirement for processing chain.
- Writing engineering documentation and technical reports in English.
Must Have Requirements
- PhD in Remote Sensing or related fields (PostDoc Experience is a plus).
- Experience with Satellite Optical data (SAR is a plus).
- Experience with Machine Learning techniques in general and Random Forest in particular.
- Proficiency with GIS.
- Proficiency with Python.
- Proficiency with tool to manipulate EO data (e.g. sen2cor).
- Good knowledge of EO data format.
- Knowledge of Rest API for querying EO data repositories.
- Knowledge of Linux shell.
- Analytical, critical and proactive mind. • Fluency in English (spoken and written) is essential.
- Very good organizational quality required.
- Very good communication skills.
- High degree of autonomy.
Being considered as a plus:
- Knowledge of other programming or coding languages such as IDL, C, C++, Fortran.
- Experience with physical modelling (e.g. hydraulic, hydrology, crop, …)
- Deep learning techniques and other AI techniques.
- PostDoc in Remote Sensing or ML.