Intern in the LEO Exploration Group

Our team and mission

The Human and Robotic Exploration Programmes, the Leader of the LEO Exploration Group shall manage the Agency’s human spaceflight activities in Low Earth Orbit (LEO) and in particular as ESA ISS Programme Manager interface with the NASA ISS Programme and other NASA Managers for negotiations of Technical Understandings as well as represent ESA at the ISS Partner Multilateral Space Station Control Board (SSCB); Chair the Exploitation Management Board (EMB) in accordance with its charter, ensuring that ISS Programme change proposals are responded to in a correct and timely manner; Act as the operational service provider towards the Research and Utilisation Group (HRE-R) to ensure timely, efficient and successful implementation of the ISS Utilisation Programme; Define the Operational Sustaining Engineering functional requirements to support the operations of the Columbus System, Infrastructure and Payloads; among others.

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. 

For further information visit our web site: http://www.esa.int

For further information on the topics:

ESA - Space training team - Electronic Field Book development

ESA - Space training team – Machine learning for recognition of planetary materials from multispectral datasets

ESA - Space training team - Planetary mineral database development and validation of spectra classification methods

Field(s) of activity for the internship

You can choose between the following topics:

1) Topic 1: Electronic Field Book (EFB) system development

The EFB is a tool supporting astronaut mission operations with technology for geolocation, cave mapping, scientific data gathering, sensor interaction and wireless data relay to mission control centres. As an intern, you will support the software or hardware development of this exploration tool to improve, extend and test its functionalities.

2) Topic 2: Machine Learning for recognition of planetary materials from multispectral datasets

As an intern, you will continue the development of machine learning algorithms for the recognition of planetary materials from multispectral datasets. This project focuses on combining several mineral characteristics to achieve automatic classification of minerals and rocks.

3) Topic 3: Development of analytical toolset for recognition of planetary materials and validation of spectra classification methods

As an intern, you will continue enhancing and developing the PANGAEA analytical toolset consisting of multi-spectral archives and the Mineralogical Database, a curated collection of reference information on planetary analogue minerals and rocks. You will also help evaluate the most suitable spectral identification method for planetary materials with the custom ML classification software, collecting and analysing the analytical data, and helping to prepare the system for the PANGAEA training course.

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 English is required. Knowledge of another Member State language would be an asset.

Educational knowledge:

1) Topic 1:
Depending on the chosen branch and profile (either software or hardware):

• Software development: academic or professional experience with at least one of the programming languages, frameworks or engines currently used in the project: JavaScript, AngularJS, Java, CouchDB, HTML, Ionic, Cordova.
• Experience on one or more of the following paradigms would be considered a plus: C++, C#, Qt, Python, REST, TensorFlow, Docker, user interface design. Previous experience in GIS systems would be a plus.
• Hardware, telecommunications, and prototyping: academic or professional experience in UNIX embedded boards or generic electronics (e.g., RaspberryPi, ESP32, Arduino), as well as having basics of OpenWRT, Wi-Fi and of routing and networking. Experience in hardware assembling and CAD 3D design-printing and prototyping. Familiarity with standards for ergonomics in terrestrial applications, and in ECSS for space utilisation would be a plus.

2) Topic 2:

• Practical experience in Machine Learning based classifications (and/or data mining, data fusion, statistics, clustering, decomposition/unmixing, recommender systems or other alternative classification methods), or in the processing and analysis of data coming from analytical instrumentation, or with databases. Academic or professional experience with the programming languages and frameworks currently used in the project:
• Python, TensorFlow, Keras, Scikit-learn, Numpy, matplotlib. Additional experience in Jupiter notebook, JavaScript, analysis and visualisation of scientific data is considered a plus.

3) Topic 3: 

• Knowledge and practical experience of using, processing and analysing data from analytical tools and instrumentation, in particular of molecular and atomic spectroscopy (VNIR, Raman, LIBS, XRF), or working with and maintaining digital information catalogues and databases are a benefit.
• Familiarisation with geochemistry, mineralogy and petrology, or attendance of courses related to planetary geology, astrobiology or planetology would be an asset.