Radar Remote Sensing Scientist

Hydrosat is a space and data analytics company building a new Earth Observation constellation and software to unlock the power of thermal infrared imagery. Our mission is to capture and deliver high spatio-temporal resolution thermal infrared data, currently not available from other sources, to provide insights that benefit the environment, enhance food and water security, and serve other critical applications. Our downstream applications team in Luxembourg combines best-in-class remote sensing, machine learning, and cutting-edge fusion approaches to thermal imagery to deliver innovative and scalable solutions to the agri-food industry.

We are looking for bright, creative, and ambitious people who can work in a dynamic and collaborative start-up environment. Hydrosat is determined to change the way people use space imagery and revolutionize agriculture. Join us on this mission and help transform the world.

As a Radar Remote Sensing Scientist, you will be an integral part of a dynamic team of scientists and engineers developing innovative commercial products for farm irrigation management, crop stress detection, and water productivity and accounting. Your role will focus on processing and analyzing Radar data in appropriate bands (e.g., Sentinel-1 and other C-band missions, L-band missions) to build vegetation and crop water stress models. You will collaborate on algorithm development to deliver actionable insights from radar remote sensing.

Responsibilities

• Process, analyze, and interpret SAR data from Sentinel-1 and other satellite missions to extract vegetation and soil information.

• Refine downscaling algorithms for L-band soil moisture algorithms.

• Develop and refine algorithms to detect crop water stress, soil moisture, and vegetation dynamics using radar data.

• Integrate SAR with other remote sensing modalities (e.g., optical, thermal) for improved monitoring of crop conditions.

• Address challenges in scaling SAR-based models across diverse climates, soil types, and crop species.

• Design and implement validation strategies using field measurements and experimental data.

• Contribute to the transition of research models into scalable, commercial applications.

• Master’s degree in Remote Sensing, Geoinformatics, Physics, Environmental Sciences, or a related field.

• Strong background in SAR data processing and analysis.

• Proficiency in Python programming for geospatial data handling.

• Familiarity with SAR principles such as backscatter, coherence, and polarimetry, and their application to vegetation and soil monitoring.

• Highly self-motivated and eager to learn, with a demonstrated ability to solve complex problems creatively.

• Strong team player with proven ability to take ownership and collaborate effectively with internal and external partners.

Desired Qualifications

• PhD in Remote Sensing, Geoinformatics, Physics, or related field.

• At least 3 years of experience working with SAR data in a research or applied setting.

• Experience with vegetation monitoring, soil moisture retrieval, or water stress modeling using SAR.

• Proficiency with geospatial and earth observation tools such as SNAP, Rasterio/GDAL, and GIS platforms.

• Experience integrating SAR with optical/thermal data for vegetation or water cycle modeling.

• Familiarity with agricultural systems, crop water use, or agronomy is a strong asset.

• Experience with cloud computing platforms (e.g., AWS, GEE).

• Proficiency in collaborative software development using version control (e.g., Git).

Benefits

• Attractive compensation package

• Equity through stock option plan – be part of our long-term success

• Fast-paced, dynamic startup environment with real impact and ownership

• Hybrid work model – 1 remote day per week

• Work-from-anywhere flexibility – up to 2 weeks per year

• EU Visa sponsorship if needed

• Attractive Luxembourg tax breaks upon relocation & relocation bonus

• Eligibility to apply for tax reduction under Luxembourg’s new impatriate tax regime for highly skilled workers