Space training team – Planetary Mineral Database Development and Validation of Spectra Classification Methods

Our team and mission

PANGAEA (Planetary ANalogue Geological and Astrobiological Exercise for Astronauts) is a geological and astrobiological field training course for astronauts and mission developers. It develops fundamental knowledge and skills in these disciplines, as well as observational and decisional skills such as identifying important geological features in the field, conducting efficient sampling and effectively communicating with scientists on Earth. Complementary to its training goals, PANGAEA is also used as a research and development platform to enable advances to be made in several technological, scientific and operational areas. 

CAVES (Cooperative Adventure for Valuing and Exercising human behaviour and performance Skills) teaches astronauts human performance and behavioural skills for exploration tasks through an expedition into a natural cave system. Cave systems present environments and situations very similar to spaceflight, making them ideal for this type of training. The scientific exploration conducted by the astronauts during CAVES also enhances human understanding of cave environments.  

Activities and learning areas

Geology and geo-microbiology research is a primary scientific goal in current satellite and rover missions to Mars, Moon and asteroids, and these disciplines will have an even greater importance in future manned planetary exploration. 

In the coming years, European astronauts will be involved in defining and planning unmanned and manned missions underpinned by geological exploration. Consequently, knowledge about general geology and planetary geology will be crucial to their role as an astronaut. Additionally, many of the Earth Observation tasks currently performed from the International Space Station have a strong relationship with geology.

Future human missions that return to the Moon or land on the surface of Mars will require astronauts to perform geological exploration during Extravehicular Activities (EVAs). With the right preparation, astronauts will be required to quickly identify key mineral resources, perform on-site analyses and collect valuable samples. This process will be greatly enhanced by portable analytical tools (VNIR, Raman, LIBS, XRF, etc.) that allow rapid mineralogical and elemental analysis of prospective samples. To make these instruments effective, they must be equipped with the appropriate libraries and software to ensure the scientific data collected is accurate and easy to interpret. This will allow improved decision making and flexecutionto be applied by the astronauts, even without the support of the scientists from ground control. To enable this, our team is working to enable the Electronic Field Book (EFB) system to record, accurately classify, enriched with relevant information, and distributed to all relevant mission support teams, spectroscopic data collected in the field. Two key projects are currently being developed to help achieve this, the PANGAEA Mineralogical Database (MinDB), and a machine learning toolset (MLtools).

The MinDB is a structured set of information on all the rocks and minerals detected on the Moon, Mars and other planetary bodies, coupled with information on most effective methods to identify them in-situ. A key part of this is library of standard spectra. These spectra are collected based on available open access on-line catalogues as well as from our own bespoke spectroscopic measurements (VNIR, Raman, LIBS & XRF) of planetary analogue minerals from different collections. The spectral library is specifically designed to improve the classification of minerals by offering a bespoke database focused on planetary materials. This project focuses on combining several mineral characteristics to achieve their fast and reliable in-situ classification.

The main task of the internship is to continue the development of the state-of-art analytical methods for recognition of planetary materials from multispectral datasets, which has been developed during previous internships. This will include: search and validating molecular and atomic spectra of minerals and their mixtures, maintaining the PANGAEA mineralogical database, and testing the developed Machine Learning software to evaluate the most suitable combination of spectral methods for identification of planetary materials.

Specific duties

Candidates will be assigned specific duties based on their background.

• Validate the spectroscopic library of relevant minerals.
• Evaluate the most effective combination of analytical methods (such as VNIR, Raman, LIBS, XRF) to identify minerals of interest.
• Update information on the rocks and minerals potentially present on the surface of the Moon and Mars, including components of magmatic rocks, meteorites, impact and weathering products.
• Integrate acquired data and spectra into a training dataset for Machine Learning software that is being developed in parallel as a part of the PANGAEA EFB.
• Preparation of the astronaut field-training course, PANGAEA, including making improvements to lesson materials, presentations and documentation.

Competencies and skills

Preferred educational background incomputer science, data science, software engineering, applied mathematics or statistics.

• Good knowledge of analytical methods and spectrometers for molecular and atomic spectroscopy, mineralogy or geo-chemistry. Experience in using or designing the spectroscopic instruments, and/or working with the information catalogues and databases.
• Attendance, during studies, of courses related to planetary geology, astrobiology or planetology would be an asset.

Internship start dates are flexible. Candidates should be available for six months. Shorter internships can be negotiated on a case by case basis, the minimum length being four months. 

Applications are open until 29 July 2024.

Click here to apply: Intern in the Space Training Team (CAVES & PANGAEA) Job Details | ESA