ESA Graduate Trainee in Future Engineering Lab & Infrastructure - Advanced Engineering Environments

Our team and mission

You will be joining the Future Engineering Division of the European Space Agency, which is responsible for shaping and delivering advanced engineering expertise, tools, methods and standards to support the preparation and development of future space missions.

The Division acts as a centre of excellence and innovation hub for future-oriented engineering, ensuring that missions are designed using cutting-edge technologies, robust engineering practices and sustainable approaches. By combining innovation with direct mission support, the team transforms new ideas into practical solutions that can be reliably applied across programmes and projects.

The Division’s mission is to enable future space missions by advancing how engineering is performed, through modern engineering environments, digital and data-driven practices, and close collaboration with industry and academia. Its vision is to position future engineering as a key enabler of European space ambitions, delivering tangible, measurable and long-term impact for future missions.

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

Field(s) of activity/research for the traineeship

During your traineeship, you will contribute to the creation and operation of the Future Engineering Laboratory, which is envisioned as a modular, scalable and world-class innovation engine. The laboratory will function as a sandbox, model testbed and showcase for advanced engineering, enabling closer collaboration between the European Space Agency and industry, and accelerating innovation for future space missions.

You will be involved in activities that support this vision, including:

• supporting the consolidation and implementation of the Future Engineering Laboratory, including requirements definition, architectural concepts and the integration of digital and physical engineering assets;
• contributing to the development of a modular and scalable laboratory architecture that can adapt to future needs and evolving technologies;
• supporting the integration of collaborative digital platforms and engineering tools to enable seamless workflows and data-driven engineering, in close collaboration with the Future Engineering Laboratory/infrastructure and Future Engineering Data Hub;
• contributing to the definition of engineering environments that support modelling, simulation and advanced engineering processes based on shared and structured data;
• supporting the use of shared infrastructure for joint pilot projects with industry, enabling experimentation, testing and technology validation;
• assisting with the definition and application of governance, security and compliance principles to ensure interoperability and the long-term sustainability of the Laboratory;
• contributing to continuous improvement activities that allow the laboratory to evolve in an agile manner in response to operational business needs;
• supporting open innovation activities, such as idea campaigns, workshops and demonstrations, to engage internal teams and external partners;
• participating in preparatory activities related to the development of a future digital model factory, aimed at streamlining design-to-production workflows, simulation and testing;
• exploring advanced engineering approaches, including model-based engineering methods, digital representations of systems and processes, immersive engineering environments and data-driven engineering techniques;
• supporting research and technology development activities related to smart manufacturing concepts, production process planning and advanced inspection methods for space systems;
• preparing technical documentation, concept notes, presentations and communication material to support decision-making, coordination and outreach activities.

Through these activities, you will gain hands-on experience in modern engineering environments and innovation infrastructure, while contributing to the transformation of how future space missions are designed, developed and prepared.

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 just completed, or be in the final year of your master’ s degree in aerospace engineering, systems engineering, computer science, data science, mechanical engineering, or a related field. Specialisation or coursework in digital engineering, AI/ML, simulation technologies, or advanced manufacturing would be an asset.

Additional requirements

Familiarity with model-based systems engineering (MBSE) concepts and tools would be an asset.

Basic understanding of digital twin technologies, simulation platforms or immersive technologies (VR/AR/XR).

Knowledge of data analytics and AI applications in engineering workflows.

Interest in advanced manufacturing concepts, such as smart factories, automation and non-destructive inspection.

Strong interest in innovation ecosystems, collaborative platforms and open innovation approaches.

Curiosity and adaptability to explore emerging technologies and methodologies.

Creative problem-solving and willingness to challenge conventional approaches.

Proactive attitude toward continuous improvement and shaping future processes.

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.