The Role

We are looking for a motivated Image Processing Intern to join our data processing and algorithm development team. The role involves helping develop pipelines that convert raw satellite optical data (L0) into L1C and L2A products. The intern will learn how satellite optical imaging systems work and apply this knowledge to processing, noise reduction, and sensor simulation.

Key Responsibilities

1.    Optical Processing Pipeline Development:

○     Help develop and test algorithms that convert raw satellite optical data (L0) into calibrated and georeferenced L1C and L2A products.

○     Work on key processing steps such as radiometric and geometric correction, geolocation, orthorectification, and atmospheric correction.

○     Write modular, testable, and efficient code for operational pipelines.

2.    Satellite Optical Imaging Systems:

○     Learn how satellite optical imaging systems form images, including the role of optics, detectors, electronics, viewing geometry, and platform motion.

○     Use this understanding to support calibration, correction, reconstruction, and product-generation algorithms.

3.    Noise Modelling and Mitigation:

○     Study and model common sensor noise, detector variations, defective pixels, quantisation effects, and imaging artefacts.

○     Develop and test methods to reduce these effects while preserving image quality.

4.    Sensor and Imaging Simulation:

○     Build simple, physics-based simulators for image formation, sensor response, sampling, geometry, and noise.

○     Use simulated and real data to test algorithms and study the effect of sensor parameters.

5.    Validation, Collaboration, and Documentation:

○     Define and use basic metrics to evaluate radiometric quality, geometric accuracy, noise, and product consistency.

○     Collaborate with the Software, Remote Sensing, Payload, and Systems teams to integrate algorithms.

○     Clearly document code, methods, assumptions, experiments, and results.

Requirements

● Pursuing a Bachelor's or Master's degree in Computer Science, Electrical or Electronics Engineering, Aerospace Engineering, Remote Sensing, Physics, or a related field.
● Good foundations in image processing, computer vision, signal processing, and mathematics.
● Proficiency in Python and C++, with familiarity with libraries such as NumPy, SciPy, OpenCV, Rasterio, or GDAL.
● Basic understanding of optical imaging, sensors, radiometry, sampling, noise, and calibration.
● Familiarity with satellite data products, coordinate systems, geometric transformations, geolocation, or atmospheric correction.
● Exposure to sensor simulation, scientific programming, or geospatial datasets is desirable.
● Coursework or experience in remote sensing, optimisation, TensorFlow, or PyTorch is a plus.

Benefits

● Contribute to real satellite Earth Observation processing systems.
● Learn from remote-sensing scientists, payload engineers, and software developers.
● Gain hands-on experience with optical data, calibration, L0-to-L1C/L2A processing, sensor modelling, and data fusion.
● Work in a dynamic and innovative space-technology startup.