Internal Research Fellow (PostDoc) in xAI and Decision Intelligence for EO Resilience applications

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 be part of the ESA Φ-lab. Our mission is to accelerate the future of Earth observation (EO) by embracing disruptive innovation and acting as the catalyst for disruptive/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 such as AI, ML, quantum computing, edge computing, metamaterials, photonics, etc. Many of the challenges posed by new technologies still 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 academics, 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 devote most of your time to the agreed research topics, but will also support the Φ-lab’s industrial and internal activities, mentor members of our research network, and participate in outreach activities that will be generally, but not exclusively, related to your research topics.

You are encouraged to visit the ESA website: https://www.esa.int/

Field(s) of activity/research for the traineeship

The European Space Agency is seeking a Research Fellow to advance innovative resilience and security applications that leverage the combined strengths of Earth observation (EO) and explainable artificial intelligence (xAI) for decision intelligence. In an era of rapidly evolving geopolitical dynamics and increasing complexity in the security landscape, the ability to transform EO data into reliable, transparent and actionable intelligence is critical. You will explore novel approaches for exploiting multi-sensor satellite data — such as optical, SAR, thermal, and hyperspectral — to support early warning, strategic situational awareness and the monitoring of emerging risks. A key focus of the fellowship will be the development of explainable AI architectures capable not only of detecting and characterising threats, anomalies and changes on Earth, but also of presenting their outputs in ways that are interpretable and trustworthy for security analysts and mission operators.

Working within ESA’s multidisciplinary research environment, you will investigate how explainability can enhance user confidence, operational uptake and the safe integration of AI-driven systems in security-oriented workflows. This includes designing methodologies that ensure traceability, robustness and bias mitigation in AI models, as well as creating prototype tools that demonstrate how transparent machine reasoning can support evidence-based decision-making. The role offers a unique opportunity to contribute to Europe’s technological sovereignty by shaping next-generation EO+xAI capabilities for resilience, and engaging with key stakeholders across the European space and security ecosystem.

Main research topics:

• EO-driven threat detection and situational awareness: develop innovative methods to exploit multi-sensor EO data (e.g. optical, SAR, thermal or hyperspectral) for detecting anomalies, emerging risks and defence-relevant activities. Emphasis will be placed on transparent, interpretable models that provide evidence-based reasoning for mission-critical decisions.
• Explainable AI for mission-critical decision support: design interpretable machine learning architectures capable of offering clear, auditable explanations of assessments and predictions, ensuring analysts and operators understand model outputs in time-sensitive security scenarios.
• Real-time intelligence fusion and rapid response: investigate methods to fuse EO data with auxiliary information — including environmental simulations and open-source intelligence (OSINT) software — to generate timely, reliable intelligence for crisis monitoring and threat evolution analysis.
• Resilience and responsible use: develop techniques to embed safeguards into EO+XAI and decision intelligence systems, addressing bias, uncertainty quantification and operational risks, ensuring outputs meet ethical and security requirements within European contexts.
• Prototype development and strategic integration: build demonstrators, validation pipelines and simulation testbeds to evaluate the performance, explainability and physical consistency of EO+xAI+decision intelligence systems, contributing to ESA’s strategic roadmap for secure, resilient and trustworthy space-based intelligence.

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

• What core research questions will you investigate, and which approaches — EO analytics, explainable AI and decision intelligence — will you use to address emerging resilience challenges?
• How can explainability techniques enhance user trust, accountability and operational uptake of AI-based threat detection, anomaly monitoring and resilience-relevant situational awareness?
• In what ways can EO+xAI+decision intelligence frameworks support reliable decision-making in dynamic or high-risk scenarios where ground truth is limited or unavailable?
• How will the integration of multi-sensor EO data and real-time environmental signals increase the accuracy, interpretability and operational value of security-relevant analyses?
• What are the main technical, ethical and operational challenges involved in deploying transparent decision AI systems for security and defence, and how can uncertainty estimation, constraints and traceability be embedded?
• How will your proposed research contribute to ESA and, more generally, Europe’s long-term security resilience and strategic autonomy, as well as the future development of explainable and trustworthy EO-based intelligence capabilities within ESA’s mission portfolio?

In particular, you will:

• undertake advanced research activities exploring and expanding the use of disruptive and transformative innovation to develop new frameworks and solutions. Your research may cover a wide range of innovative topics:
  • exploring innovative methodologies and technologies;
  • developing novel methods, new technology implementations (such as ML models) and high-level products;
  • contributing 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 lab activities and the 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;
• participate in internal research sprints to explore, test and validate novel EO concepts, algorithms and workflows in a fast-paced, collaborative environment;
• support the Φ-lab’s daily activities and research network of European graduate trainees, interns and visiting researchers, as applicable;
• advance multi-sensor EO threat detection and real-time intelligence fusion using transparent, interpretable AI to support time-critical, defence and crisis decision-making;
• develop and validate EO+xAI decision intelligence demonstrators with built-in resilience, ethical safeguards, and operational robustness aligned with European and ESA strategic priorities.

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, Earth system science, climate etc., with a thesis subject relevant to the tasks outlined above.

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, AI, ML, quantum computing, 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;
• The interest 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.