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[AIMLAC CDT Studentship] Design of open science standards for specialised brain imaging data

   Cardiff School of Physics and Astronomy

About the Project

The UKRI CDT in Artificial Intelligence, Machine Learning and Advanced Computing (AIMLAC) aims at forming the next generation of AI innovators across a broad range of STEMM disciplines. The CDT provides advanced multi-disciplinary training in an inclusive, caring and open environment that nurture each individual student to achieve their full potential. Applications are encouraged from candidates from a diverse background that can positively contribute to the future of our society. 

Characterising structures at the cellular scale is key to understanding tissue properties in health and disease. Performing such a characterisation in vivo and non-invasively is an extremely challenging enterprise. Central to this mission is magnetic resonance imaging (MRI), which has shown its value for depicting tissue microstructure in unprecedented detail. The versatility of MRI has attracted a variety of scientists, creating a diverse landscape of acquisition and processing methods. The large heterogeneity in notations and acquisition parameters employed in the literature makes the adoption of data sharing practices a priority with the aim of facilitating scientific reproducibility and maximising efforts and investments in the area. Despite the attempts to solve this issue, scholars in the field of microstructural MRI have not embraced such open practices, mainly due to the lack of a robust and general methodology that can be adapted to heterogeneous data description as needed in MRI.

In this project, the student will develop and utilise data archiving standards for specialised MRI data acquired to depict tissue microstructure. More specifically, the candidate will generate a comprehensive and generalised data archiving framework for openly storing and sharing microstructural MRI information under the Brain Imaging Data Structure (BIDS) umbrella. This framework will allow to record all the data and metadata needed to replicate the MRI experiments performed, simplifying the data sharing and processing stages. This includes the description of all the time varying fields tuned in the scanner and relevant for understanding the recordings. The standard will work with multimodal contrasts used in the research area, with special emphasis in diffusion MRI and spectroscopy. In a later stage, the resulting standard will be used to automatise data processing algorithms depending on available acquisition parameters, paving the way for the application of Machine Learning methods.  

The PhD project will take place in the Cardiff University Brain Research Imaging Centre (CUBRIC), a pioneer in brain imaging research. CUBRIC houses >200 researchers across Schools and Colleges, making it a vibrant multidisciplinary research community. Moreover, the centre hosts state-of-the-art MRI equipment that the student will benefit from.

The successful candidate will have a unique training opportunity, involving access to a heterogeneous and continuously growing MRI data archive, tuition for specialised MRI operation and sequence design, presenting research work in international conferences, establishing links with industrial partners (e.g., SIEMENS), and being part of the larger collaboration in the area.

Start date: 1st October 2023 

The UKRI CDT in Artificial Intelligence, Machine Learning and Advanced Computing provides 4-year, fully funded PhD opportunities across broad research themes: 

  • T1: data from large science facilities (particle physics, astronomy, cosmology) 
  • T2: biological, health and clinical sciences (medical imaging, electronic health records, bioinformatics) 
  • T3: novel mathematical, physical, and computer science approaches (data, hardware, software, algorithms) 

Its partner institutions are Swansea University (lead institution), Aberystwyth University, Bangor University, University of Bristol and Cardiff University. 

Training in AI, high-performance computing (HPC) and high-performance data analytics (HPDA) plays an essential role, as does engagement with external partners, which include large international companies, locally based start-ups and SMEs, and government and Research Council partners. Training will be delivered via cohort activities across the partner institutions. 

Positions are funded for 4 years, including 6-month placements with the external partners. The CDT will recruit 10 positions in 2023. 

The partners include: JD Power UK, ATOS, DSTL, Mobileum, GCHQ, EDF, Amplyfi, DiRAC, Agxio, STFC, NVIDIA, Oracle, QinetiQ, Quantum Foundry, Dwr Cymru, TWI and many more. 

More information, and a description of research projects, can be found at the UKRI CDT in Artificial Intelligence, Machine Learning & Advanced Computing website. 

How to apply: 

To apply, and for further details please visit the CDT website follow the instructions to apply online.  

This includes an online application for this project at (with a start date of 1st October 2023):

Applicants should submit an application for postgraduate study via the Cardiff University webpages including: 

• your academic CV 

• a personal statement/covering letter 

• two references, at least one of which should be academic 

• Your degree certificates and transcripts to date. 

In the "Research Proposal" section of your application, please specify the project title and supervisors of this project. 

In the funding section, please select that you will not be self-funding and write that the source of funding will be “AIMLAC CDT” 

The deadline for applications for the UKRI CDT Scholarship in Artificial Intelligence, Machine Learning and Advanced Computing (AIMLAC) is mid-February 2023. However, AIMLAC will continue to accept applications until the positions are filled. 

For general enquiries, please contact Roz Toft   


The typical academic requirement is a minimum of a 2:1 physics and astronomy or a relevant discipline. 

Applicants whose first language is not English are normally expected to meet the minimum University requirements (e.g. 6.5 IELTS) (

Candidates should be interested in AI and big data challenges, and in (at least) one of the three research themes. You should have an aptitude and ability in computational thinking and methods (as evidenced by a degree in physics and astronomy, medical science, computer science, or mathematics, for instance) including the ability to write software (or willingness to learn it). 

For more information on eligibility, please visit the UKRI CDT in Artificial Intelligence, Machine Learning & Advanced Computing website 

Funding Notes

The UK Research and Innovation (UKRI) fully funded scholarships cover the full cost of 4 years tuition fees, a UKRI standard stipend of currently £17,668per annum and additional funding for training, research and conference expenses. The scholarships are open to UK and international candidates.


J Gholam, F Szczepankiewicz, CMW Tax, L Mueller, E Kopanoglu, M Nilsson, S Aja-Fernandez, M Griffin, DK Jones, L Beltrachini, “aDWI-BIDS: an extension to the brain imaging data structure for advanced diffusion weighted imaging”, arXiv:2103.14485v2, 2021.

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