Job Title: Agricultural Remote Sensing Scientist
Location: Luxembourg, Luxembourg
Job Type: Permanent
Salary: €90,000 +Benefits + Relocation package
Working setup: 4 days per week onsite / 1 day Remote
Language: English
Industry Sector: New Space, Earth Observation, Satellite Imagery, Remote Sensing
Introduction:
Talent-Relay has partnered with Global Earth Observation client to onboard an Agricultural Remote Sensing Scientist into their expanding science and research team, in Luxembourg.
Our partner leverages satellite imagery, thermal infrared and multi-spectral data, to deliver valuable insights into agriculture, climate, and commercial clients.
The team is responsible for developing advanced algorithms to transform satellite data into actionable information.
We require an Agricultural Remote Sensing Scientist to developing innovative commercial products for farm irrigation management, crop stress detection, and water productivity accounting.
Your responsibilities will include collaborating on the development of algorithms to provide actionable insights based on remote sensing data.
If you’re passionate about applying machine learning to real-world challenges in agriculture, climate, and safety, this role is for you.
Key Responsibilities
Use remote sensing platforms and field data and to develop evidence-based models for water consumption and demand in field crops.
- Design and enhance commercial algorithms to detect soil moisture and water stress in crops using remote sensing data, optimizing farm-level irrigation management.
- Address challenges in scaling algorithms to diverse climatic conditions, soil types, and crop species.
- Coordinate, analyse, and provide expert advice on farm field experiments to validate algorithms under real-world conditions.
Required Qualifications, Skills and Experience
- Advanced degree (Master’s/Ph.D.) in Agricultural or Environmental Sciences, Physics, Remote Sensing, or a related field.
- Understanding of surface energy balance principles or the water cycle within the soil-plant-atmosphere system.
- Strong skills in Python, statistics, and problem-solving.
- Ideally have experience in processing satellite imagery (e.g., Sentinel, Landsat) using tools like GDAL, Geopandas and Rasterio.
- Ideally have a good understanding of land-cover classification or time-series forecasting.
- Familiarity with software development practices (e.g. Git, version control, CI/CD).
Desirable Skills and Experience
- Strong foundation in surface energy balance modeling, soil physics, hydrology, or related domains
- Working knowledge with AWS or other cloud provider (GCP, Azure).
- Familiarity with remote sensing, thermal imaging, or statistical analysis
- Agricultural Knowledge: Familiarity with the agricultural sector and agronomical best practices