Descripción de la oferta
ESA Graduate Trainee in Software Engineering for AI Applications in Science Operations
Job Requisition ID: 20232Date Posted: 1 February 2026Closing Date: 28 February 2026 23:59 CET/CESTPublication: External OnlyType of Appointment: ESA Graduate TraineeDirectorate: ScienceWorkplace: Villanueva de la Cañada, SpainGrade Band: F1 - F1
Our team and mission
ESA maintains a world‑leading Science Programme with missions in heliophysics, planetary science, astrophysics, and fundamental physics. The Department for Science Operations and Office for Science Engagement and Oversight host the scientists and engineers that oversee the space missions, from study to end of operations. The X‑ray Multi‑Mirror Observatory (XMM‑Newton) is one of ESA’s major science missions. Staff and contractors at ESAC supporting the XMM‑Newton Science Operations Centre (SOC) are responsible for all aspects of science operations, including proposals, planning, Target of Opportunity handling, instrument monitoring, scientific calibration, analysis software development, data processing, and distribution via the archive facilities.
Field(s) of activity/research for the traineeship
The traineeship will develop a system that provides an interface between Large Language / Large Reasoning Models and the operational data of XMM‑Newton. The system will ensure the veracity of information returned by the models and will support two demonstration applications:
Development of a system that allows a user to ask questions about the operational status of XMM‑Newton posed in speech and natural language, verifies answers, and generates results verbally or graphically.
Enhancement or simplification of a process in the XMM‑Newton Science Operations Centre through the use of Large Reasoning Models or Large Language Models and the XMM‑Newton operational data.
To achieve this, you will study selected science operations processes, supporting data, and data sources. You will need to interact with the science operation system developers and operations engineers to complete this study.
Responsibilities
Design and develop the interface system between AI models and XMM‑Newton operational data.
Implement verification mechanisms to ensure the accuracy of AI‑generated responses.
Execute the two demonstration applications described above.
Collaborate with developers, engineers, and scientists to integrate the system into existing workflows.
Document design choices, technical specifications, and user guides.
Qualifications
Education: Recent graduate or final year of a master’s degree in Computer Science, Artificial Intelligence, or a related field.
Technical competencies: Knowledge of relevant technical/functional domains; general knowledge of the space sector; familiarity with ESA programmes and projects.
Behavioural competencies: Result orientation, operational efficiency, fostering cooperation, relationship management, continuous improvement, and forward thinking.
Good interpersonal and communication skills; experience working in multicultural international teams is an asset.
Additional Requirements
Strong motivation, a clear professional perspective, and career goals will be explored during the later stages of the selection process.
Diversity, Equity and Inclusiveness
ESA is an equal opportunity employer, committed to diversity and inclusion. We welcome applications from all qualified candidates irrespective of gender, sexual orientation, ethnicity, religion, age, disability, or other characteristics. Assistance can be provided for applicants with disabilities.
Important Information and Disclaimer
During the recruitment process, applicants may be required to undergo selection tests. Successful candidates will also need to undergo basic screening through an external background screening service in compliance with ESA security procedures.
Nationality and Languages
Only nationals of ESA Member States or specified partner states are eligible. The working languages are English and French; a good knowledge of one of these is required.
Legal and EEO Statements
ESA is a European Union-owned organisation, and the recruitment of staff must take into account an adequate distribution of posts among nationals of the ESA Member States. Short‑listing for an interview will give priority to external candidates from under‑represented Member States.
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