Intern, Earth Observation Projects – Event-Aware On-Board Processing for CHIME

European Space Agency - ESA

. Join the Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) project .

Posted 10/31/2026internshipNoordwijk • NetherlandsEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in machine learning, computer vision, and signal processing, with practical experience in Python and deep-learning frameworks. Capable of collaborating with engineering teams to evaluate mission performance and develop reproducible software and validation packages.

Highest-signal resume keywords

Machine LearningComputer VisionSignal ProcessingPython ProgrammingHyperspectral Data

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningComputer VisionSignal ProcessingPython ProgrammingDeep-Learning FrameworkModel CompressionTransfer LearningUncertainty EstimationData PrioritizationDetection Performance Quantification

Soft Skills

CollaborationCommunication

Industry Keywords

Hyperspectral ImagingEarth ObservationEnd-to-End Mission PerformanceArtificial Intelligence ProcessingScientific TraceabilityEuropean Export Control Regulations

Tech Stack

Tools & technologies

PythonRemote Sensing

About the role

Key responsibilities & impact

Join the Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) project
Work with system and satellite engineering teams on on-board artificial-intelligence processing and end-to-end mission performance evaluation
Define configurable processing modes for land, ocean and night-time observations
Integrate compact detection methods into the mission end-to-end simulator
Connect detection masks with selective compression and data-prioritisation policies
Quantify detection performance, false alarms, scientific-data preservation and potential downlink savings
Assess robustness across geographic regions, seasons, illumination conditions and representative instrument effects
Define operating limits, verification criteria, traceability information and fallback behaviour
Deliver reproducible software, trained models, documented datasets and a technical report suitable for public presentation or publication
Potentially develop a staged validation concept using reference and candidate processing configurations, including possible use of the two-satellite constellation
Collaborate with mission engineers, data-processing specialists and Earth-observation scientists
Produce a reproducible prototype and validation package demonstrating event-aware processing value while maintaining scientific traceability and controlled operational complexity

Requirements

What you’ll need

Must be a university student, preferably in the final or second-to-last year of a Master's-level university course
Must be able to prove enrolment at university for the entire internship duration
Good knowledge of English or French required
Knowledge of another ESA Member State language is an asset
Background in machine learning, computer vision, signal processing or remote sensing
Practical experience with Python and a deep-learning framework
Familiarity with hyperspectral data, transfer learning, model compression or uncertainty estimation is an asset
Must be eligible to access information, technology and hardware subject to European or US export control and sanctions regulations
Applications considered only from nationals of Austria, Belgium, Cyprus, Czechia, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, the Netherlands, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, Switzerland, and the United Kingdom

Benefits

Comp & perks

Internship opportunity with ESA
Access to mission simulation tools, curated datasets and results of previous internships
Opportunity to work with mission engineers, data-processing specialists and Earth-observation scientists
Opportunity to deliver work suitable for public presentation or publication
Inclusive working environment and disability support during the workplace and recruitment process