Intern in the Space Training Team, Machine Learning (CAVES & PANGAEA)
Porz-Wahn, DE
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.
Candidates interested are encouraged to visit the ESA website: http://www.esa.int
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:
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.
Candidates should possess practical experience in classification techniques, particularly those based on Machine Learning supervised classification.
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
ESA is an equal opportunity employer, committed to achieving diversity within the workforce and creating an inclusive working environment. We therefore welcome applications from all qualified candidates irrespective of gender, sexual orientation, ethnicity, beliefs, age, disability or other characteristics. Applications from women are encouraged.
At the Agency we value diversity, and we welcome people with disabilities. Whenever possible, we seek to accommodate individuals with disabilities by providing the necessary support at the workplace. The Human Resources Department can also provide assistance during the recruitment process. If you would like to discuss this further, please contact us via email at contact.human.resources@esa.int.
Important Information and Disclaimer
During the recruitment process, the Agency may request applicants to undergo selection tests.
Applicants must be eligible to access information, technology, and hardware which is subject to European or US export control and sanctions regulations.
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
Please note that applications are only considered from nationals of one of the following States: Austria, Belgium, Czechia, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, the Netherlands, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, Switzerland, and the United Kingdom.
