Multi-scale and dynamic imaging techniques have been demonstrated to be one of the powerful tools in materials characterisation. However, the images cannot always satisfy the scientific of industrial requirement. Large datasets of scientific measurements (e.g. 3D/4D imaging, physical and chemical) on varied rocks have been collected to help us to understand how geothermal energy, hydrogen, carbon capture and storage, and storage solutions for wind, solar and tidal energy can reduce our carbon emissions. This project aims to use machine learning based method to enhance the images resolution (super-resolution), predict the 3D microstructure of rocks, accelerate the image processing and build workflow to upscale chemical and physical properties from pore-scale to field-scale.
The student will be provided full training on the 3D/4D image acquisition and processing, and will have access to National X-ray Computed Tomography Facility (https://nxct.ac.uk/), National institute for Advanced materials research and innovation (https://www.royce.ac.uk/), and Diamond light source (www.diamond.ac.uk).
More details can be found here (https://www.research.manchester.ac.uk/portal/en/researchers/lin-ma(87434d6c-9ea2-4291-92a2-481374db4fe5)/projects.html?period=running) and can be further discussed via email or video calls. Strong applicants will be recommended to university scholarship competition.
Applicants should have or expect to achieve at least a 2.1 honours degree (or equivalent) in earth sciences, environmental sciences, petroleum engineering, chemical engineering, civil engineering, mechanical engineering, materials or machine learning. Research experience in machine learning is desirable.
Successful candidates will join the ‘Digital Rock Manchester’ group and will be enrolled in the 3.5-year Ph.D. program of the School of Chemical Engineering at University of Manchester.
Information about the application process and a link to the online application form can be found at https://www.manchester.ac.uk/study/postgraduate-research/admissions/how-to-apply/.
You MUST make contact with the lead project supervisor before submitting an application.
When completing the application include the name of the lead project supervisor as the potential supervisor.
Enquiries about this project can be sent to Dr Ma - firstname.lastname@example.org as the lead project supervisor. The Admissions team in Chemical Engineering can be contacted at email@example.com with any queries you may have regarding the application process.
Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact. We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.
We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder).