Experts (f/m) for the development of modular process chains in cloud environments in the field of (semi-) automatic image analysis based on remote sensing data
The satellite constellations of today in the field of earth observation, such as ESA's high-resolution Sentinel satellites, as well as small satellite constellations with very high temporal and spatial resolution, offer new possibilities for automated image analysis and information extraction. The processing of these large volumes of data requires the use of parallelisable process environments in a cloud-based infrastructure, and is complemented by deep learning / machine learning techniques.
For a number of years, GAF has been heavily involved in the production of land cover layers with Europe-wide coverage (so-called High Resolution Layer in the Copernicus Land area) based on high-resolution and very high-resolution satellite data, and develops processing chains in this context that are as automated as possible. Further areas of focus in the development of automated process chains relate to the monitoring of forest areas (REDD+) in Africa and the recording of agricultural parameters for the insurance industry.
To strengthen our development team in the field of (semi-)automatic analysis of remote sensing data and the creation and implementation of modular process chains, we are now looking for motivated experts with a focus on remote sensing, data analysis and software programming.
- Development and customisation of, as well as provision of assistance for, modular process chains for thematic image analysis and for supporting automatic evaluation procedures
- Development of specific evaluation modules/workflows for thematic image analysis with a focus on optical data and/or SAR, mainly in Python (or R)
- Interface linking with Python
- Quality assurance of output products
- Documentation of workflows and tools
- University degree in computer science, geoinformatics, geography, forest and environmental sciences, cartography, agriculture, surveying or similar, preferably with a focus on remote sensing and one of the following disciplines: forestry, agriculture, land use, geography
- Minimum 2 years of professional experience
- Very good knowledge of the mathematical/physical basics of remote sensing and the thematic analysis of satellite imagery
- Very good programming skills, especially in Python
- Ability to work in an independent and responsible way
- Innovative thinking
- The ability to communicate and work in a team within a complex project environment
- Very good spoken and written English skills and good German skills
- Experience in the application of machine and deep learning procedures and techniques
- Practical experience with the Python modules numpy, scipy, (geo-)pandas, sklearn, gdal and/or similar
- Knowledge about the processing and evaluation of SAR data
- Knowledge about OpenSource software, such as Orfeo, QGIS, SNAP
- Basic knowledge of geodatabases (e.g. PostGIS) and SQL
- Practical experience in dealing with remote sensing data and the processing of GIS data as part of a degree thesis, internships or previous work experience
+49 (0) 89-121528-0
What we offer:
- a young and motivated team that works according to agile principles
- a relaxed, friendly and respectful working atmosphere
- good development opportunities and the opportunity to contribute and make use of your own ideas and skills
- interesting and responsible tasks in an exciting and technically cutting-edge environment
- mentoring to ensure your solid and rapid integration into our company and in your area of responsibility
- performance-related remuneration and regular training
- a modern workplace in the conveniently located Munich West area (near Hirschgarten)
- flexible working hours within the conditions of our flexitime scheme
- and much more
Would you like to work with us?
In that case, please send your application documents, including details of your earliest possible starting date and salary expectations, to recruitinggaf [dot] de. Please state: “Development of modular process chains in cloud environments” in the email subject field.