Our team and mission

This position is based at the European Space Research and Technology Centre (ESTEC) – Noordwijk, Netherlands

Space technology, and satellite communications in particular, have a big impact on our daily lives today. The satellite communications sector is the most dynamic and commercial segment of the space industry, with evolving business strategies, the emergence of new actors, and shifting user demands driving profound change.

The Market Intelligence team develops actionable evidence including market intelligence, financial analysis, socio-economic impact assessments, databases, and reports to support the activities of the Connectivity and Secure Communications (CSC) Directorate of ESA. As part of our dynamic, collaborative, and passionate team, you will help to shape the future of the space industry through cutting-edge market intelligence activities.

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

Field(s) of activity for the internship

You can choose between the following topics:

1) Topic 1: Data Science applied to satellite telecommunication market analysis

The market intelligence team provides analysis needed to support the European satellite telecommunications community to make strategic decisions. You will contribute to internal studies analysing satellite communications and telecom business trends to produce concise, timely market information that will inform ESA management and representatives of ESA’s Member States. Such investigations and data sciences analysis will include but also go beyond the satcom sector to focus on non-space sectors such as automotive.

As a recent example, an internal analysis has been performed on the quality of the cellular network experienced by drivers across several European countries, identifying areas of lost connectivity. This analysis aimed to supporting ESA, ARTES Member States, and Industry in assessing the need for satellite communications as a complement to the terrestrial network to ensure seamless and ubiquitous automotive connectivity.

In this internship, you will work on similar projects to the example above. Such analysis may be shared with ESA management, representatives of ESA’s Member States or/and European and Canadian industry.

2) Topic 2: Natural Language Processing (NLP) and Large Language Model (LLM) applied to satellite communications

Recently, the space sector has been evolving at a rapid pace. This change has mainly been triggered by the emergence of New Space actors from various parts of the world and an enormous rise of start-ups into the space economy. This new era has also seen the re-emergence of system concepts, such as constellations, embarking further advanced technologies including new frequency bands, Artificial Intelligence, and autonomous collision avoidance. For commercial satellite applications, it is becoming more and more challenging to keep track and understand the underlying movements, initiatives, actors, and technology developments worldwide.

In that context, ESA has been studying Natural Language Processing (NLP) and Large Language Model (LLM) to respond to such dynamism and capitalise on state-of-the-art Machine Learning (ML) capabilities. Your project will focus on continuing the investigation and development of these capabilities and apply them to the satellite communications domain.

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 in your final or second-to-last year of a university course at Master’s level and you need to remain 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 Member State language would be an asset.

Background and knowledge of the space industry, experience undertaking market research, knowledge and background in python would also be an asset for both topics.

For Topic 2: Knowledge and background in Natural Language Processing (NLP) and/or Large Language Models (LLM) would be an asset.