Internal Research Fellow; PostDoc) in Onboard Agentic AI Autonomous EO Constellations
Job in
00044, Frascati, Lazio, Italy
Listed on 2026-09-01
Listing for:
Altro
Full Time
position Listed on 2026-09-01
Job specializations:
-
Research/Development
Data Scientist, Research Scientist, AI Business & Operations
Job Description & How to Apply Below
Location: Frascati
Our team and mission
Reporting to the Head of the Explore Office in the ESA Φ-lab, you will work in close cooperation with other staff in the Directorate of Earth Observation Programmes. You will also cooperate with scientists and engineers from EOP-FA (the System Architect Office) at ESTEC, and potentially with staff in other parts of ESA.
Location
ESRIN, Frascati, Italy
Our team and mission
Reporting to the Head of the Explore Office in the ESA Φ-lab, you will work in close cooperation with other staff in the Directorate of Earth Observation Programmes. You will also cooperate with scientists and engineers from EOP-FA (the System Architect Office) at ESTEC, and potentially with staff in other parts of ESA.
You will be part of the ESA Φ-lab, whose mission is to accelerate the future of Earth Observation via transformative innovation and commercialisation actions strengthening ESA Member States’ world-leading competitiveness.
Our vision is to be the “EO innovation hub” connecting EO with a growing ecosystem of disruptive and transformative innovations such as AI, machine learning, quantum computing, edge computing, metamaterials and photonics. Many of the challenges posed by new technologies need to be tackled at scientific, application and capability levels to deliver the maximum value from satellite-derived EO assets for our climate, society and economy.
The Φ-lab brings together early career and senior researchers from a variety of disciplines across EO in pursuit of disruptive/transformative innovation to contribute to the development of novel EO solutions.
We Offer
a stimulating multinational, interdisciplinary and open work environment;
access to high-performance computing infrastructure and unparalleled EO and technology expertise;
a unique opportunity to work on innovative solutions to address global challenges;
freedom and focus to conduct creative research while making an impact in relation to ESA’s strategy;
a wide network of relationships and collaboration with top academia, industry and research centres;
the opportunity to contribute to the Φ-lab strategy and activities.
As an internal research fellow within the Φ-lab, you will invest your time mainly in the agreed research topics but will also provide support to the Φ-lab’s industrial and internal activities, mentor members of our research network and engage in outreach activities, all generally but not exclusively related to your research topic.
You are encouraged to visit the ESA website at https://(Use the "Apply for this Job" box below)./
Field(s) of activity/research for the traineeship
The objective of this research fellowship is to advance intelligent, agentic AI-driven, goal-oriented mission planning for EO satellite constellations, with a strong focus on autonomy, responsiveness, and coordinated execution across multiple space assets. The research will centre on the design and implementation of onboard AI systems that enable the autonomous management of mission planning, data acquisition, and satellite tasking in real time.
The fellowship will investigate how mission planning can evolve from static scheduling to an adaptive, intelligence-driven process executed directly on board satellites. This includes the development of onboard AI systems capable of continuously monitoring payload data, platform status, and environmental conditions, and autonomously updating mission plans accordingly. These systems will combine AI-based decision-making, learning approaches, and predictive capabilities to enable spacecraft to react proactively to events while reducing reliance on ground intervention.
A key focus will be the autonomous coordination of multi-satellite constellations through onboard intelligence. The typical scenario this research will address is how, once an event is detected by a “tip” satellite, onboard AI systems can coordinate “cue” satellites by determining the optimal response: identifying which satellites should be tasked, when observations should occur, and which asset can capture the event first.
This requires distributed onboard AI capabilities for task allocation, resource management, and real-time constellation coordination.
The fellowship will also…
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