Status: Closed
Applications open: 11/09/2023
Applications close: 27/10/2023
About this scholarship
Project tittle: Artificial intelligence, Machine learning, and Computer vision for subsurface characterisation This project aims to develop computer vision applications for geological characterisation using state-of-the-art AI/ML methods applied to energy resource quantification and identification and qualification of potential subsurface CO2 and hydrogen storage locations. The work will assimilate data from multiple sources: cores scanned with x-ray tomography, infrared spectroscopy, high-resolution stereo imaging, optical and electron microscopy on rock cores, and cuttings samples to build data-driven models to classify rock types from images and to predict rock physical properties. The successful applicant will have the opportunity to develop a prototype of a tool that allows automated lithology classification from optical and infrared images of drill cores and cuttings. They will be involved in dataset acquisition, including core/cuttings preparation, imaging, and labelling. Computer vision algorithms, such as R-CNN, YOLO, SSD, will be used for individual particle/feature detection/recognition. Predictive AI/ML algorithms will be developed, trained on labelled datasets, and applied to unknown images for real-time lithology classification. The state-of-the-art imaging facilities, including experimental rigs of Curtin University, CSIRO, and Geological Survey of Western Australia, will be used for this project. The project benefits from collaboration between several Australian governmental institutions, which will allow the candidate to develop and grow a professional network and working relationships with a diverse multidisciplinary team of scientists. The candidate is expected to have knowledge of artificial intelligence, machine learning, computer vision, automated subsurface characterisation, and drill cores.
- Current Students
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Faculty of Science & Engineering
- Science courses
- Higher Degree by Research
- Australian Citizen
- Australian Permanent Resident
- New Zealand Citizen
- Permanent Humanitarian Visa
- International Student
- Merit Based
- The successful candidate will receive a stipend of $33,000 per annum (tax free).
- The duration of the award shall be for three years with a possible extension of up to six months (maximum), assessed on a case by case basis.
- In addition, this scholarship will include a tuition fee offset support for a successful international candidate.
Scholarship Details
1
The successful candidate must enrol into a Doctor of Philosophy (PhD) program (full-time study mode).
The successful candidate must meet the minimum academic entry requirement for admission into the Doctor of Philosophy program https://research.curtin.edu.au/postgraduate/ including the English proficiency levels set by Curtin University.
Candidates should have:
- Master and bachelor (First Class Honours) degree in Physics, Geophysics, Computer Science, Engineering, or equivalent degree.
- Language requirement (IELTS, Overall 6.5, Speaking, Writing, Reading and Listening 6.0 or TOEFL, Overall 79, Reading, 13, Listening 13, Speaking 18, Writing 21).
Students with below skills are encouraged to apply:
- Background in physics, geophysics, mechanics or mechanical engineering, or a related discipline
- Good math skills
- Some experience in scientific programming
- Experience in laboratory measurements – a plus
- Previous research experience and publications.
Application process
Please send your expression of interest with your CV, publication list, and English score to Name: Prof. Boris Gurevich, email [email protected]
Enrolment Requirements
The successful candidate must enrol full-time into the PhD program at Curtin University and meet their Milestone 1, 2 and 3 requirements.
Changes to Enrolment
The successful candidate must enrol full-time into the PhD program at Curtin University and meet their Milestone 1, 2 and 3 requirements.
Enquiries
For further information please contact: Prof. Boris Gurevich, email [email protected]
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