Intern in The Space Training Team, Machine Learning

Vor 7 Tagen

Wahn, Deutschland European Space Agency Vollzeit

**EUROPEAN SPACE AGENCY**

Intern in the Space Training Team, Machine Learning (CAVES & PANGAEA)

**Job Requisition ID**:19645

**Closing Date**:11 July 2025 23:59 CET/CEST

**Publication**:External Only

**Type of Contract**:Intern

**Date Posted**:13 June 2025

**Location**
- EAC, Porz-Wahn, Germany

**Our team and mission**
The CAVES and PANGAEA team specialises in training programmes that equip astronauts and mission developers with scientific, expeditionary and behavioural skills. The group’s primary output is focused around two training programmes, CAVES, a course that uses natural cave systems for expeditionary and human behavioural and performance training, and PANGAEA, a course for geological and astrobiological field training. Complementary to their training goals, these programmes are used as research and development platforms to advance several of ESA’s technological, scientific and operational areas.- **Field(s) of activity for the internship**

**Topic of the internship: Machine Learning for recognition of planetary materials from multispectral datasets.**
Interns are sought to contribute to the ongoing development of Machine Learning algorithms for recognition of planetary materials from multispectral datasets. This project focuses on combining diverse mineral characteristics to enable automatic classification of minerals and rocks.For detailed information on this internship position, please click here:
ESA - Space training team - Planetary Mineral Database Development and Validation of Spectra Classification Methods**Behavioural competencies**
Result Orientation
Operational Efficiency
Fostering Cooperation
Relationship Management
Continuous Improvement
Forward ThinkingFor 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.Relevant experience includes, but is not limited to, data mining, data fusion, statistics, clustering, signal decomposition/unmixing, incremental few-shots learning, or other alternative classification methodologies.Experience in processing and analyzing data derived from analytical instrumentation, or working with databases, is also valuable.Academic or professional proficiency with the programming languages and frameworks currently used in the project is required, specifically Python, TensorFlow, Keras, Scikit-learn, Numpy, and matplotlib.Additional experience with Jupyter notebooks and the analysis and visualization of scientific data would be considered a plus.Experience in integrating MLOps software and datasets together will be considered a valuable asset.**Diversity, Equity and Inclusiveness**

**Important Information and Disclaimer**
- During the recruitment process, the Agency may request applicants to undergo selection tests.
- The information published on ESA’s careers website regarding working conditions is correct at the time of publication. It is not intended to be exhaustive and may not address all questions you would have.

**Nationality

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