ESA Graduate Trainee in Artificial Intelligence & Quantum Computing for Space Exploration
Job Requisition ID: 19325
Date Posted: 1 February 2025
Closing Date: 28 February 2025 23:59 CET/CEST
Publication: External Only
Type of Contract: ESA Graduate Trainee
Directorate: Human and Robotic Exploration
Workplace:Porz-Wahn, DE
Grade Band: F1 - F1

EDUCATION

You should have just completed, or be in the final year of your master’ s degree in a relevant field such as data science, computer science, artificial intelligence, business analytics, or other related disciplines. A solid academic foundation in AI, machine learning, or software development will be beneficial to this role.

ADDITIONAL REQUIREMENTS

• AI and Machine Learning: A solid understanding of machine learning algorithms, frameworks, and techniques, with practical experience in developing and deploying AI solutions. Candidates should have hands-on experience with AI projects, demonstrating not only knowledge of “what” is being done, but also a clear understanding of “why” it is being done and “how” to implement it effectively.
• Programming Knowledge: Proficiency in Python, R, or other languages used for data science and machine learning applications.
• Quantum Computing: Familiarity with Quantum Computing principles and their applications, with a particular focus on innovative use cases such as planetary navigation and optimisation challenges. Hands-on experience with quantum computing platforms (e.g., IBM Q, Google Quantum AI) is a plus.
• Prototyping and Development: Experience in developing prototypes and MVPs for AI applications, with a strong focus on understanding the problem at hand and applying appropriate AI solutions to address it. Proven ability to work on real-world AI projects with a clear understanding of the technical challenges involved.
• Communication Skills: Excellent written and verbal communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders. The ability to clearly articulate the rationale behind AI decisions and methodologies is essential.
• Self-Organisation: Strong self-organisation skills with the ability to manage multiple tasks, prioritise work, and meet deadlines. Proactive in identifying and addressing obstacles.
• Collaboration and Coordination: Ability to work effectively in a multi-disciplinary, multi-cultural team environment, supporting cross-functional knowledge exchange and contributing to the development of AI solutions across different departments within ESA.
• Learning Mindset: A strong desire to learn and grow within the field of AI, with a focus on both technical development and practical application of AI solutions in the context of space exploration.
• Problem-Solving: A proactive attitude toward identifying challenges and applying well-understood AI techniques to solve complex problems, while being mindful of the constraints and requirements specific to space exploration.Fluency in English is required, and knowledge of other languages would be advantageous.
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  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.

• Assisting in the development of AI-driven prototypes and simulations to demonstrate the core capabilities of an application or system, ensuring it meets the specific requirements before full-scale development;
• Applying general AI and machine learning techniques either independently or in collaboration with experts to develop smaller-scale AI applications with for example in fields such as predictive analytics, anomaly detection, or data-driven decision support;
• Supporting the definition of high-level requirements and specifications in preparation for tenders with industry, helping to ensure that the scope and objectives of AI projects are well coordinated and clearly outlined;
• Participating in progress meetings, reviews, and tests to verify the functionality of AI applications, ensuring alignment with project goals and requirements;
• Collaborating with cross-functional teams to ensure that best practices and standardisation are followed across ESA projects, supporting the coordination of these efforts;
• Supporting the identification and initiation of new opportunities and projects to integrate AI into space exploration missions based on the findings from previous studies;
• Investigating and contributing to the further materialisation of Quantum Computer utilisation, particularly for planetary navigation on the Moon for Rovers, as part of efforts to explore innovative applications for advanced computational technologies