Our team and mission

The Product Assurance Sections coordinate and supervise Product Assurance and Safety (PA&S) activities for the relevant programmes and projects within their respective application directorates. They also represent the directorates in all corporate PA&S activities, including quality management.

The Exploration & Science PA Section is responsible for the quality management and PA&S functions throughout the design, development, and operation of projects within the Directorate of Human and Robotic Exploration Programmes (HRE). As a Research Fellow, you will lead the development of advanced assurance methodologies for the safe use of artificial intelligence (AI) and autonomous functions in human spaceflight systems. Your work will bridge the gap between conventional deterministic safety assurance approaches and emerging data-driven and autonomous technologies, helping to define future ESA frameworks, standards, and practices for crewed missions.

Field(s) of activity/research for the traineeship

In particular, your research activities will include:

• conducting a comprehensive literature survey and state-of-the-art assessment of AI and autonomy assurance approaches across relevant domains, including space, aviation, automotive and other safety-critical industries, and identifying their applicability to, and gaps in relation to, ESA practices;
• defining a classification framework for AI-enabled and autonomous functions in human spaceflight systems, distinguishing between advisory, supervisory and safety-critical roles, and establishing the associated levels of assurance, verification and acceptance criteria;
• developing hazard analysis methodologies tailored to AI-based systems, extending traditional approaches, such as FMEA and FTA, to address non-deterministic behaviour, data-driven failure modes, human-machine interaction and emergent system effects;
• proposing and assessing architectural patterns for the safe integration of AI functions within crewed systems, including the use of deterministic safety monitors, runtime assurance mechanisms, bounded autonomy concepts and human-in-the-loop supervision;
• devising and validating verification and validation (V&V) strategies for AI-enabled functions, including scenario-based testing, robustness assessment, dataset qualification, fault injection and performance evaluation under off-nominal and degraded conditions;
• developing safety assurance case methodologies for AI and autonomous systems, defining the required claims, arguments and evidence to support acceptance within ESA human spaceflight programmes, in alignment with evolving practices within and outside ESA;
• analysing representative use cases, such as onboard fault detection and diagnosis, autonomous rendezvous support and crew decision support systems, and demonstrating the application of the developed methodologies to realistic mission scenarios;
• investigating the impact of AI-enabled autonomy on human reliability and operational concepts, including crew interaction, trust, workload and decision-making in nominal and contingency situations;
• contributing to the definition of lifecycle processes for AI-enabled systems, including configuration control, model updates, retraining constraints and operational monitoring during missions;
• providing recommendations for the evolution of ESA PA&S practices, including potential input into guidelines, handbooks and future standardisation activities.

Technical competencies

Behavioural competencies

Result Orientation

Operational Efficiency

Fostering Cooperation

Relationship Management

Continuous Improvement

Forward Thinking

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

Education

You should have completed within the past five years, or close to completing, a PhD in aerospace engineering, computer science, artificial intelligence, systems engineering, software engineering or a related field, with a demonstrated focus on AI, autonomy or complex software systems.

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 good interpersonal and communication skills and should be able to work in a multicultural environment, both independently and as part of a team. Previous experience of working in international teams can be considered an asset. Your motivation, overall professional perspective and career goals will also be explored during the later stages of the selection process.

You should also have:

• solid knowledge of artificial intelligence and machine learning techniques, including their limitations, validation challenges and applicability to safety-critical systems;
• experience in the development, verification or validation of software-intensive or autonomous systems, preferably in safety-critical domains such as space, aviation, automotive, rail or medical;
• experience with data analysis and modelling tools, such as Python or MATLAB, including handling of datasets used for training, testing and validation of AI models;
• an understanding of verification and validation techniques for AI-enabled systems;
• familiarity with human-machine interaction concepts and the role of human operators in supervisory or decision-making loops;
• an interest in human spaceflight and safety-critical applications, and the motivation to help advance ESA’s PA&S practices;
• the ability to work autonomously while interacting effectively within multidisciplinary teams, including software engineers, system engineers, safety engineers and mission operations specialists.