Our team and mission

This position can be based:

• At the European Space Research and Technology Centre (ESTEC) – Noordwijk, Netherlands
• At the European Space Astronomy Centre (ESAC) – Near Madrid, Spain

Under the direct authority of the Director of Science, the Science and Operations Department is responsible for ensuring that maximum scientific return, within applicable constraints, is maintained as an objective for the Directorate’s missions through their lifetime, by providing scientific oversight of the Directorate’s missions throughout their lifecycle, managing and being responsible for the operation of the Directorate’s missions once successfully commissioned, and curating the scientific data in their legacy phase, while establishing and maintaining the necessary science interfaces to the community. These responsibilities are discharged in full coordination with the Directorate’s Departments and Offices and, as appropriate, with the Directorate of Operations.

In implementing its duties, the Science and Operations Department is supported by the:

• Science Division
• Mission Operations Division
• Science Operations Development Division
• Data Science and Archive Division
• Mission Support Office

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: Exploring and organising Mercury’s surface scientific holdings for Bepicolombo (ESAC)

MESSENGER observations of Mercury have paved the road for the ESA/JAXA BepiColombo mission to further explore the characteristics of Mercury’s surface. A large diversity of scientific interests feed a very active scientific community that is analysing the available observations to better plan for BepiColombo. The MeSS (Mercury Surface Spectroscopy) project is providing easy and effective access to scientific data for scientists. Successful investigations of Mercury’s surface have revealed the great potential of using relational databases for new scientific analysis although organizing all those useful datasets is complex.

The aims of this internship are to expand the content of the MeSS database hosted at ESAC by incorporating scientific maps and to provide open access to the service. Among your tasks will be to incorporate new scientific products to the PostgreSQL relational database and develop the next version of the MeSS database within the ESA Datalab infrastrcture. Through your technical expertise, scientific interests and open minded approach you will provide solutions in incorporating data products of different natures into the MeSS database. You will be able take key decisions in the technical development of the MeSS infrastructure that fulfill the needs of the scientific community. New products are being developed by numerous scientists continously and it is expected that the selected trainee will be versatile enough to incorporate these news products (e.g, machine learning outputs, laboratory measurements) into the database during the internship. You will be associated with the Science Ground Segment of the BepiColombo mission and participate in the preparation of BepiColombo while focusing on enhancing the science exploitation of previously acquired data.

For more information on this topic, please visit: Exploring and organising Mercury’s surface scientific holdings for Bepicolombo

.

2) Topic 2: Developing a Velocity Field Visualization Environment for GNSS Observations: A Digital Navigation Project (ESAC)

Are you passionate about cutting-edge technologies and eager to contribute to geohazard monitoring using state-of-the-art GNSS data? Join our exciting trainee project at the GNSS Science Support Centre (GSSC) and be part of a transformative initiative that enhances the accessibility of up-to-date GNSS observations for critical geohazard services.

What is the project use case, goal and impact? The primary objective of this trainee project is to integrate GSSC Now’s repository with other Navigation repositories to ensure timely availability of high-quality GNSS observations (RINEX data) from a relatively dense network. The goal is to create a dataset aligned with the global coverage of Earth Observation (EO)-based Geohazard services. The velocity field, a critical product derived from the integrated dataset, could play a pivotal role in supporting Earth Observation Platforms (EOP) with comprehensive monitoring and estimation of terrain deformations. Geohazard professionals, scientists, and decision-makers will rely on this essential information for assessing geological risks, ensuring public safety, and making informed infrastructure-related decisions.

How would you achieve it? You will work closely with our experienced team to establish seamless integration between GSSC Now and other Navigation repositories, optimizing data retrieval processes for real-time updates. By harmonizing the GNSS observations, the resulting dataset will support the development of a powerful visualization environment within GSSC Now. This environment will enable the generation of the velocity field of a given station network over a provided time series.

For more information on this topic, please visit: Developing a Velocity Field Visualization Environment for GNSS Observations: A Digital Navigation Project

.

3) Topic 3: A Gaia view of the constellations across time (ESTEC)

Ever since humanity has been observing the night sky, the stars have been a limitless inspiration. As a result, today’s set of well-known constellations are the end product of a millennia-long journey involving storytelling and mythology and represent a unique mix of our global cultural heritage. Nonetheless, as a result of the motions of stars on the sky, exquisitely measured by ESA’s billion star surveyor, Gaia, the constellations are not static configurations but (slowly) evolve over time.

This internship aims to explore this evolution, which is not visually susceptible over the lifetime of humans and hence not easy to grasp, using Gaia data. You will develop, implement, test, document, and run Python software (a Jupyter Notebook) to visualise, in a scientifically accurate way, the stellar content of arbitrary constellations at arbitrary moments in time, up to (dozens or hundreds of) millennia in the past or future. As an example, it will answer the question which object on the sky will be the first to cross a constellation boundary (and when), it will visualise the Orion constellation as observed by the Mesopotamians, and it will provide a powerful tool to demonstrate the dynamic nature of the night sky. As such, the project , which may ultimately evolve into an interactive tool or web plugin, will have a high outreach value and will constitute an important showcase for ESA and its ground-breaking science missions.

For more information on this topic, please visit: A Gaia view of the constellations across time

Behavioural competencies

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

Education

You must have student status and be enrolled at university for the entire duration of the internship. You should preferably be in your 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:

• Knowledge of PostgreSQL database management and programming language(s) allowing connecting and handling PostgreSQL (e.g. python) will be needed
• An interest in planetary science and scientific research is an important asset
• Knowledge and interest in data mining, data visualisation and a Geographical Information System (GIS) would be highly beneficial
• Experience in developing Python Notebooks will be considered

2) Topic 2:

• We are looking for a proactive trainee with a background in space science data processing, global navigation satellite systems, geodesy, remote sensing or a related field
• Proficiency in programming languages such as Python, experience in data integration, and a strong interest in geohazard monitoring and digital platforms are highly desirable

3) Topic 3:

• This project is deemed most suitable for a student in astronomy with an interest in data visualisation
• Affinity with Python (and the ADQL query language) is an asset but the traineeship offers ample room for improving these skills