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Data Science & Archive Division to Build Visualisation Tools

Sustainable Future Platform: Data Science & Archive Division to Build Visualisation Tools
SFP-1-7-540x343 Data Science & Archive Division to Build Visualisation Tools
Position: Data Science & Archive Division to build visualisation tools
Internship ID: 19068
Salary: Indefinite
Location: (ESAC) – Near Madrid, Spain
Time Type: Indefinite
Contract Type: Intern
Duration: Indefinite
Institution: European Space Astronomy Centre  (ESAC)
Start Date: Indefinite
Deadline: 30 November 2024

This position is based at the European Space Astronomy Centre  (ESAC) – Near Madrid, Spain.

Under the direct authority of the Directorate of Science, the Head of the Science Operations Department is responsible for the development of the science operations infrastructure under the Directorate’s responsibility, the operation of the Directorate’s missions once successfully commissioned, and the curation of all scientific data in the missions’ legacy phase. These responsibilities are discharged in full coordination with the Directorate’s Departments and Offices and as appropriate, with the Directorate of Operations (D/OPS).

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

  • Mission Management and Science Operations Division (SCI-SO);
  • Science Operations Development Division (SCI-SD);
  • Data Science and Archives Division (SCI-SA).

Field(s) of activity for the internship

The topic of the internship: Planetary visualisation with ESA Datalabs

The ESA Datalabs platform currently supports access to all public data in the Planetary Science Archive (PSA), from the earliest mission (the Giotto flyby of comet Halley) to the latest (JUICE, on its way to the Jupiter system). A Jupyter Lab environment has already been set up to work with planetary data, but the Datalabs platform supports many other application types.

This internship would aim to evaluate different options (e.g. a Python Flask app) which could be used to visualise data from the PSA (e.g. interactive time-series visualisation, geospatial display etc.) and to prototype one or more. Python code to work with the archival data formats (PDS3 and PDS4) are already available and you would be free to work on any instrument or data type you have an interest in. The ideal output would be an application published in the Datalabs catalogue which integrates with the archive via its APIs and filesystem and visualises data in a user-friendly way.

Required Qualifications

You must be a university student, preferably in your final or second-to-last year of a university course at the 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.

Knowledge of Python, Docker, Scientific visualisation, and Planetary science would be an asset.

Behavioural competencies

  1. Result Orientation
  2. Operational Efficiency
  3. Fostering Cooperation
  4. Relationship Management
  5. Continuous Improvement
  6. Forward Thinking

For more information, please refer to ESAthe   Core Behavioural Competencies guidebook.


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