Remote Sensing Specialist for Forest Monitoring

**Description**:
This is an opportunity for a **Forester/Ecologist with Remote Sensing experience** to further develop his/her technical/project skills and professional career in an international active company. To strengthen our capacities in the field of (semi-) automatic analysis of remote sensing data and the creation and implementation of modular processing chains, we are now looking for motivated experts with a focus on remote sensing, data analysis, optimising and implementing processing chains, with also a strong forestry and environmental background.

**Your tasks**:

- Implementation of modular process chains for forest/land cover thematic image analysis and for supporting automatic evaluation procedures by close communication with our development teams by provision of assistance for further process enhancements
- Support of conceptual development of workflows for automation of image processing process chains (e.g. time-series analysis, bulk image classification)
- Implementation of specific evaluation modules/workflows for thematic image analysis with a focus on optical data and/or SAR, mainly in Python
- Organising and implementing the EO forest/land cover product generation under consideration of budget, schedule and resources
- Implementation of Quality Control and Quality Assurance of output products
- Support of project reporting and documentation of workflows and tools

**Benefits**:
**What to expect**:

- Variety instead of everyday routine in exciting projects in one of Europe’s leading geo-information companies
- Comprehensive support when you start at GAF, as part of our mentoring programme
- Personal responsibility and freedom to contribute and implement your own ideas
- Training and development - your experience and knowledge count
- A multicultural and respectful working environment and an interdisciplinary team of committed colleagues
- Working cross-functional with other in-house teams
- A leadership style based on trust
- Flexible working hours as part of our flexitime policy, to make it easier to combine work and your private life
- Operational health management
- Company pension scheme (optional), travel health insurance with worldwide coverage
- Excellent public transport connections
- An attractive location in the western part of central Munich, with great opportunities for outdoor activities and recreation, including in the close vicinity
- ... and, last but not least: be your own barista Enjoy fair trade organic coffee made in our traditional Italian espresso machine

**Requirements**:
**Requirements**:

- Educational background: Minimum MSc. in forestry, ecology or similar, with a focus on remote sensing and one of the following disciplines: tropical forestry, land use
- Profound / deeper understanding of modular process chains for thematic image analysis
- Minimum 5 years of relevant working experience
- Advanced knowledge of the mathematical/physical basics of remote sensing and the thematic analysis of satellite data
- Profound knowledge on machine learning, neural networks, ensemble learning techniques
- Advanced practical experience in remote sensing, GIS, EO data processing, tropical forest, land use/land cover classification, damage assessment, tree species classification
- Excellent reporting and communication skills
- Autonomous and self-responsible working as well as team working skills
- Excellent command of English
- Demonstrated report writing skills and experience

**Desireable knowledge**:

- Programming experience and skills, especially in Python
- Work experience using Jupyter Notebooks
- Knowledge of geodatabases (PostGIS/PostgreSQL), GeoServer, OGC Standards
- Experience with Running ML/AI Applications in Kubernetes with e.g. Kubeflow, Tensorflow Serve
- French or Spanish language skills would be an asset

**Duration**:
**Further information**:

- Engagement at the earliest possible date
- Full-time position, 40 hours per week

**Please contact**:
Ms Ulla Weingart

recruitinggaf [dot] de

**Phone**:
+49 (0)89 12 15 28 0

**Further details**:
**Are you interested in this position?