Our team and mission

Within the European Space Agency’s (ESA)’s Directorate for Human and Robotic Exploration, the Exploration Science activities are a cornerstone of the Explore2040 strategy, driving innovation at the intersection of human exploration and scientific discovery. It integrates exploration-focused science, essential for future missions, with exploration-enabled science, leveraging space for groundbreaking research. With access to ground-based analogues, the ISS, future commercial LEO platforms, the Moon, and Mars, the programme offers unique opportunities for transformative research in diverse environments. Guided by European values of collaboration, excellence, and responsibility, the programme emphasises open science, international cooperation, and inspiring future generations. From developing countermeasures for spaceflight to searching for life on Mars, ESA Exploration Science advances knowledge for space and Earth alike.

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

Field(s) of activity for the internship

Topic of the internship: Exploration Science Strategy Consolidation supported by AI

We are offering an internship opportunity to support the consolidation of the Human and Robotic Exploration science strategy. You will help bring together a broad set of inputs, including ESA white papers, existing science strategy and roadmap documents, strategy documents from other space agencies, and peer-reviewed scientific articles. The objective is to organise these sources into a coherent knowledge base, extract the main scientific priorities and recurring themes, and support the preparation of concise synthesis material that can inform future science planning.

Tasks include:

• collect, catalogue and structure relevant strategy documents, white papers, roadmaps and scientific articles related to HRE science;
• compare the priorities, science questions, capabilities and implementation approaches identified across ESA material and documents from other agencies;
• map the scientific literature against the main HRE science themes to highlight evidence, trends, gaps and emerging topics;
• prepare clear summaries, tables, and visual synthesis material to support discussions within the team and contribute to the consolidation of future science strategy documents;
• apply existing AI/Machine Learning tools to identify knowledge gaps;
• through this work, you will learn how science strategy is developed in an international space agency context and how scientific evidence, community inputs and programme constraints are translated into strategic priorities.

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 must be a university student, preferably studying at master’s level. In addition, you must be able to prove that you will be enrolled at your University for the entire duration of the internship.

Additional requirements

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

During the interview, your motivation for applying to this role will be explored.

Knowledge and background required:

• master’s level background in data science, space science, life sciences, physical sciences, engineering, or another discipline relevant to human and robotic exploration;
• good ability to review, analyse and synthesise scientific literature, white papers, roadmaps and strategy documents;
• interest in human spaceflight, microgravity research, exploration science, or the development of science strategies for space programmes;
• good command of Microsoft Office tools, in particular Word, Excel and PowerPoint, for document preparation, source tracking, tables and synthesis material;
• basic knowledge of artificial intelligence, machine learning, and statistics methods.

Assets:

• experience with reference management and literature review tools, such as Zotero, Mendeley, EndNote, Web of Science, Scopus, or similar platforms, would be an asset;
• familiarity with artificial intelligence-assisted tools for literature screening, document analysis, summarisation, text mining or knowledge organisation would be an asset, together with the ability to use such tools critically and responsibly;
• proficiency in Python or other relevant programming languages.