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 divisions of ESA.

You will be part of the ESA Φ-lab. Our mission is to accelerate the future of Earth Observation (EO) by embracing disruptive innovation and serve as the catalyst for disruptive and transformative innovation in the sector.

Our vision is to become an EO innovation hub, connecting EO with a growing ecosystem of disruptive and transformative innovation, including 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 will bring together early career and senior researchers from a variety of disciplines across EO and disruptive/transformative innovation to contribute to the development of innovative 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: https://www.esa.int/

Field(s) of activity/research for the traineeship

Main Objectives of the Research Fellow Activity:

Cognitive Cloud Computing in Space (3CS) refers to the integration of AI, novel computing paradigms, such as cloud computing and edge computing, computing hardware, and other technologies on board space systems. By increasing satellite systems’ intelligence and enabling cooperation among different space assets, 3CS has the potential to enable novel mission paradigms, such as space-based data centres, and novel observation strategies, for example virtual constellations, and significantly enhance space’s infrastructure autonomy, responsiveness and efficiency. Such novel capabilities can directly benefit multiple EO applications such as disaster monitoring and emergency response, maritime and land surveillance.

The primary objective of this research fellowship is to design and implement onboard AI systems for the autonomous management and coordination of EO heterogenous and federated constellations. These systems, composed of cognitively enhanced satellite constellations, will operate under uncertainty to deliver critical services such as climate monitoring, disaster response, resilience tasks and resource management. Leveraging real-time environmental signals, AI agents and predictive models, the onboard AI will define action plans, optimise sensor tasking, and interact intelligently with users, marking a shift from command-driven to autonomous EO operations. Building on this, the fellowship will also explore applications in fragile or complex environments, where the AI system will process EO and contextual data to anticipate climate-related risks and suggest context-aware, goal-driven responses. It aims to support both humanitarian efforts and institutional resilience, bridging early warning with operational decision-making.

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Main Research Topics:

• Autonomous EO decision-making: develop onboard AI systems, including AI agents, visual language models and foundation models, and define mission architectures, protocols and interfaces for the orchestration and coordination of open and heterogeneous satellite constellations capable of making autonomous decisions under uncertainty.
• Multi-satellite coordination and rapid response: enable tip and cue and other novel autonomous observation strategies, onboard data fusion and embeddings aggregation, whereby heterogeneous satellite constellations collaborate and adapt in real time to dynamic events, minimising reliance on ground control. 
• Predictive models: integrate predictive Earth system models to improve responsiveness for 3CS use cases.
• Simulation and strategic integration: build testbeds for autonomous EO validation and contribute to ESA’s strategy for climate-resilient, AI-enhanced missions.

As part of your application, please provide a research proposal of no more than five pages, responding to 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, ethical and operational challenges in developing autonomous EO frameworks, and how can safeguards be embedded to address both humanitarian and security needs?
• 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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In particular, you will:

• undertake advanced research activities exploring and expanding the use of disruptive and transformative innovation such as AI, machine learning, quantum computing and edge computing to develop new frameworks and solutions. Your research may cover a wide range of innovative topics and include:
  • exploration of innovative methodologies and technologies;
  • the development of novel methods and new technology implementations of high-level products, for example machine learning models;
  • contributions to the development and curation of open data sets and tools enabling the community to develop its own AI for applications and research;
• support the definition and implementation of rapid prototyping activities, research sprints and open challenges of innovative EO solutions, addressing upcoming laboratory activities and wider strategy;
• engage with the innovation ecosystem to promote the uptake of new techniques and capture the latest developments in EO and disruptive/transformative innovation;
• publish the research project outcomes in high-impact journals;
• drive collaboration within the Φ-lab community and ESA internal teams to promote the uptake of these new techniques and solutions;
• contribute to the Φ-lab strategy, activities and outreach on disruptive technologies for EO;
• maintain a continuous dialogue with the scientific community, including major international programmes and initiatives in the field;
• support the Φ-lab’s daily activities and research network of ESA graduate trainees, national trainees, interns and visiting professors, experts and researchers, as applicable;
• design and develop onboard AI systems that autonomously optimise EO system tasking and data collection, using decision intelligence to make real-time decisions based on environmental signals and predictive models;
• contribute to the rapid prototyping and testing of AI-driven EO systems, with a focus on the autonomous decision-making capabilities that enable satellites to adapt to dynamic environmental changes and urgent events;
• collaborate closely with ESA’s Φ-lab and internal teams to integrate onboard AI and decision intelligence.

Technical competencies

Behavioural competencies

Result Orientation
Operational Efficiency
Fostering Cooperation
Relationship Management
Continuous Improvement
Forward Thinking 

For more information, please refer to ESA Core Behavioural Competencies guidebook

Education

You should have recently completed, or be close to completion of a PhD in a related technical or scientific discipline. Preference  will  be  given  to applications submitted by candidates within  five  years of receiving their PhD. In particular for this position, the following is required:

PhD in data science, AI, computer science, machine learning, aerospace engineering, Earth system science or climate, with a thesis subject relevant to the above description of tasks.

Additional requirements

In addition to your CV and your motivation letter, please prepare a research proposal of no more than 5 pages. This proposal should be uploaded to the "additional documents" field of the "application information" section.

You should have:

• Sound knowledge of themes of interest, such as EO, space missions, satellite systems, AI, machine learning, ICT revolution technologies and edge computing;
• The ability to think outside the box and explore new avenues, with natural curiosity and a passion for new subjects and research areas;
• Experience with one or more general-purpose programming languages, for example Python, and general-purpose deep learning frameworks, such as Tensorflow or PyTorch;
• Interest in and ability to share knowledge with other ESA organisational units

You should also have good interpersonal and communication skills and should be able to work in a multi-cultural environment, both independently and as part of a team. Your motivation, overall professional perspective and career goals will also be explored during the later stages of the selection process.