Our team and mission

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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 (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 address the design of onboard and system-level orchestration architectures, investigating centralised, distributed, or hybrid approaches for coordinating autonomous satellite operations. The research will explore how onboard AI can enable scalable, resilient and adaptive constellation management through intelligent decision making and cooperation among space assets.

While not the primary focus, the research may also explore additional onboard functionalities that can further improve operational performance, such as the integration of predictive models, orbital dynamics knowledge, or drag-aware optimisation strategies to enhance manoeuvre timing and mission responsiveness.

Building on this, the fellowship will also explore applications in fragile or complex environments, including resilience and dual-use scenarios,



where the AI system will process EO and contextual data to anticipate climate-related and security-relevant risks, and suggest context-aware, goal-driven responses supporting both civilian and institutional operational needs.

Ultimately, the research aims to enable a new paradigm of EO operations in which onboard AI systems form the core intelligence layer of mission planning, continuously integrating data, predictions and system knowledge to drive autonomous, coordinated and efficient satellite operations.

Main Research Topics

- Onboard Agentic AI for Mission Planning and Autonomous Management Develop onboard AI systems possibly based on agentic AI for autonomous mission planning, data acquisition and satellite tasking, adapting observation strategies based on real-time inputs and priorities.
- Smart Monitoring and AI-Based Control Design intelligent frameworks to monitor EO data, spacecraft status, and contextual information, enabling autonomous event detection, replanning and optimisation.
- Distributed Onboard AI for Multi-Satellite Orchestration Develop architectures for autonomous satellite coordination, including centralised, distributed, and hybrid orchestrator approaches for scalable constellation management, including tip-and-cue operations, enabling rapid optimised event response.
- Advanced Onboard Functionalities for Operational Enhancement Explore additional onboard capabilities, including predictive models, adaptive optimisation, and optional integration of orbital dynamics considerations.
- Simulation, Learning and Operational Validation Develop AI-enabled simulation environments and testbeds to validate autonomous mission planning under realistic operational constraints.

Within your application, please provide a research proposal (no more than 5 pages) answering the following questions:

- Describe your main research questions and how you would like to address them.
- What technological innovations in onboard AI will overcome current EO system limitations and enhance autonomous decision making, operational efficiency and responsiveness?
- How can AI-driven EO systems adapt in real time to uncertain, fragmented, or high-risk environments, including those with limited ground-truth data?
- What role will predictive models and real-time environmental signals play in improving the accuracy and value of EO-based actions?
- What are the main technical and operational challenges in developing autonomous EO frameworks, and how can safeguards be embedded to address both humanitarian and security needs? xysqume
- How will this research shape the long-term sustainability, adaptability and strategic value of EO in future space missions and global climate response?

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📌 Internal Research Fellow (PostDoc) in Onboard Agentic AI for Autonomous EO Constellations (Frascati)
🏢 Independent Space News
📍 Frascati