Our team and mission

This position is based at the European Astronaut Centre (EAC) – Near Cologne, Germany

The Software and Artificial Intelligence Team, drives innovation in HRE projects and initiatives across diverse exploration destinations such as LEO, the Moon, Mars, and Earth analogues. The team develops and integrates advanced software and AI technologies to support flight experiments, operational tools, and simulators. By creating and executing strategic plans, we ensure alignment with ESA and HRE objectives, while exploring and using cutting-edge technologies like AI, XR (eXtended Reality), IoT (Internet of Things), and Quantum Computing to enhance mission capabilities for both flight and ground segments.

As a central hub for software innovation, the team collaborates with internal and external tech experts to highlight the crucial role of advanced software in exploration. The team is structured around four core pillars: AI, XR, IoT, and Quantum technologies, with data serving as a foundational element throughout. This comprehensive approach ensures the effective integration of state-of-the-art technologies, positioning the team at the forefront of exploration advancements.

The Team for AI and Software aims to recruit 3 candidates. An internship duration of six months is preferred. 

For Topics 1 and 2, you will be working with the AI section which is part of the Team for AI and Software in the Directorate for Human and Robotic Exploration. AI plays a crucial role in enabling future space missions. From mission planning, smart space station companions and chatbots to automated navigation and route planning on other planets, it will be key to integrate AI-solutions into the future exploration roadmap. 

For Topic 3, you will be working with the XR-Lab which is part of the Team for AI and Software in the Directorate for Human and Robotic Exploration. 
 

For further information visit our web site: http://www.esa.int

Field(s) of activity for the internship

You can choose between the following topics:

1) Topic 1: Develop AI solutions for human spaceflight operations using Large Language Models (LLMs)

Operating space stations such as the ISS or the Lunar Gateway requires the management, updating, and creation of vast amount of documentation. Working with the various different datasets can be very time-consuming. You will support the team that works on implementing solutions based on large language models to make this data more accessible and improve astronaut-related operations in general. You may be involved in the day-to-day project activities and / or might have the chance to develop prototypes to extend functionality. 

2) Topic 2: Support the identification and development of a solid data infrastructure in support of future AI solutions

To prepare the Directorate for Human and Robotic Exploration (HRE) for the future use and implementation of AI-enabled solutions, it is crucial to ensure that the data required for any such activities will be available, accessible, and that there is an appropriate governance framework in place. You will work with the team to identify which data is already available and which data will need to be gathered in the future to allow for the use of innovative software and in particular AI solutions. By identifying the gap between current data management practices and requirements for future application development, you will develop technical and governance propositions to allow the directorate to use machine learning applications at scale in its space exploration missions. To ensure coherence and compatibility of infrastructure developments across all of ESA, you will work and coordinate with a variety of stakeholders across different teams. 

3) Topic 3: Exploration of visualization techniques for large technical drawings, 3D files and datasets

Spacecrafts can have very large and complex designs files, making technical assessments tedious due to the amount of design data to be handled by computers. In this topic, you will investigate advanced techniques for visualizing very large data sets and design files to allow ESA engineers to better visualize technical aspects of future spacecrafts and incorporate the designs in data-driven simulations. Your responsibilities will include a deep dive and analysis of state-of-the-art methods to visualize large datasets and complex designs (such as technical drawings larger than 10GB), and integrate them with databases of technical facts and test scenarios. You will identify the tools that best fit the current or near-future XR-Lab infrastructure and determine how to best integrate and use them. You will investigate platforms such as Nvidia Omniverse and Unreal Engine Datasmith, to assess their potential use-cases for AI-driven simulations and AI-aided design. 

Behavioural competencies

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

Education

Candidates must have student status and be enrolled at university for the entire duration of the internship. Applicants should preferably be in their final or second to last year of a university course at master’s level in a technical or scientific discipline.

Additional requirements

The working languages of the Agency are English and French. A good knowledge of one of these is required. Knowledge of another Member State language would be an asset.

Additional requirements:

1) Topic 1:

• Background in data science, software engineering, artificial intelligence, or related field.
• Strong knowledge of natural language processing and machine learning (techniques as well as applications).
• Experience with LLMs and the development of chatbots (eg. Llama.cpp).
• Ability to develop prototype applications to validate feasibility.
• Proven technical skills including proficiency in relevant programming languages such as Python, Jupyter or C++

2) Topic 2:

• Background in data science, computer science, information systems, innovation studies, or related field.
• Demonstrated experience with SQL, Python (pandas, numpy), or R for data analysis.
• Understanding of databases and cloud-based storage solutions.
• Familiarity with data management practices, including data collection, cleaning, and transformation.
• Awareness of machine learning concepts (even at a high level) and how data supports AI models.
• Ability to create clear and informative visualizations using tools like Matplotlib, Seaborn, or Tableau is considered a plus.
• Awareness of data governance stakes and potential mitigations is considered a plus
• Ability to clearly explain highly technical and complex topics in a straightforward and understandable manner.
• Understanding of space industry and exploration missions is considered a plus.

3) Topic 3: 

• Background in computer science, data science, or related field.
• Demonstrated experience in working with Unreal Engine 5 (Blueprints, Materials, UMG )
• Knowledge of a CAD tools is required (eg. CATIA, Solidworks, Inventor)
• General familiarity with 3D modelling, rendering, and game development processes.
• Knowledge of machine learning techniques is an asset
• Experience with cloud computing is an asset
• Experience with the git / git-lfs version control system is considered a plus