2024 RTP round - Characterising the habitability and of Mars throughout time using layered ejecta craters and multi-sensor satellite datas

Status: Closed

Applications open: 7/07/2023
Applications close: 25/08/2023

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About this scholarship
Description/Applicant information

The extent of habitable conditions on other planets in the solar system – in particular, the existence of water environments – is a fundamental question for planetary exploration, guiding NASA’s current and planned Mars Sample Return missions and future human exploration.  Mars is now known to have hosted localized, short duration liquid water environments at its surface and shallow subsurface, with potentially extensive liquid water environments deep in its crust, however the duration, depths and geographic distribution of these environments are still poorly known, as are their potential habitability.  Identifying locations where water and conditions that could potentially support life have occurred near the surface of Mars, or have persisted for significant periods of time, are of high importance: not just for their scientific significance in understanding the potential implications for biology, but also for identifying shallow subsurface water resources that could be accessed by crewed missions.  Secondly, there is a diversity of satellite sensors gathering data across the electromagnetic spectrum, at differing spatial, spectral, and temporal resolutions.  There is a compelling need to combine the data from different sensors to generate new products that have optimised spectral and spatial resolution and mitigate the limitations inherent to any one single sensor. 

The primary aim of the research project is to map the extent of the habitable regions of Mars throughout time using water/ice related impact morphologies, and identify regions where potential habitable environments may have persisted near to the surface, or for long periods of time.  The secondary aim is to develop new algorithms and satellite data products using machine learning based multi-sensor fusion algorithms to combine the products from different sensors on different satellites thereby filling data acquisition gaps. 

The objectives of this work are to quantify the extent of potentially habitable environments (PHEs) within the crust of Mars, where a habitable environment can be considered most broadly as one which supports: liquid water of varying plausible chemistries (brines), within a range of temperatures appropriate for terrestrial microorganisms.  The existence of habitable conditions will be probed using a subset of impact craters that likely to have formed from the presence of water/ice in the subsurface.  A range of satellite datasets will be used by the candidate to constrain the depth to, water concentration, salinity of, and age of the PHE, including: impact crater morphometry, mineralogy, rock and grain-sizes and their distribution.  The remote sensing datasets used will include: high resolution camera imagery, elevation, thermal inertia, and multi-and hyperspectral data across the visible, shortwave infrared and thermal wavelengths from a range of sensors and satellites.  The candidate will take existing machine learning image fusion algorithms, and further develop them to the unique application of infilling the particular temporal, spectral and spatial gaps of Mars satellite sensors to generate novel satellite data products at enhanced spectral and spatial resolutions than what is currently available.  The output of the work will be maps of high priority PHE that occur near-surface, or zones where PHEs cluster and or conditions of habitability are likely to have persisted for a significant period of time. 

The outcomes of this work are significant for enhancing the knowledge capacity of past, present, current and future space-based datasets, through the development of innovative algorithmic tools specifically designed to address the wide gaps in satellite data coverage, thereby improving the potential knowledge and insights from future Australian’s sensors and contributing key new knowledge for both the Australian and the global space sector. 

This project may provide an internship opportunity. 

Student type

• Future Students

Faculty

• Faculty of Science & Engineering
  • Engineering courses

Course type

• Higher Degree by Research

Citizenship

• Australian Citizen
• Australian Permanent Resident
• New Zealand Citizen
• Permanent Humanitarian Visa

Scholarship base

• Merit Based

Value

The annual scholarship package (stipend and tuition fees) is approx. $60,000 - $70,000 p.a.

Successful HDR applicants for admission will receive a 100% fee offset for up to 4 years, stipend scholarships at the 2023 RTP rate valued at $32,250 p.a. for up to a maximum of 3 years, with a possible 6-month completion scholarship. Applicants are determined via a competitive selection process and will be notified of the scholarship outcome in November 2023. 

For detailed information, visit: Research Training Program (RTP) Scholarships | Curtin University, Perth, Australia.

Scholarship Details
Maximum number awarded

1

Eligible courses

All applicable HDR courses

Eligibility criteria

We are looking for enthusiastic, passionate and self-motivated candidates with strong data analysis skills and experience with one or more programming languages (e.g. python, R, matlab, etc.).  A background in physics or geology is highly desired.  A familiarity with satellite datasets (Earth or planetary), and machine learning is desired but is not mandatory. 

Application process

This project has identified a preferred candidate and is no longer available.  Please review remaining scholarships projects .

Enrolment Requirements

Eligible to enrol in a Higher Degree by Research Course at Curtin University by March 2024.

Recipients must complete their milestone 1 within 6 months of enrolment and remain enrolled on a full-time basis for the duration of the scholarship.

Enquiries

The Project lead has identified a preferred candidate and is no longer accepting applications. Please click here to review remaining scholarships projects.

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