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Research Associate in Multi-Modal Medical Image Registration

King's College London - Research Department, Surgical & Interventional Engineering

Location: London
Salary: £44,355 to £51,735 per annum including London Weighting Allowance
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 11th June 2025
Closes: 29th June 2025
Job Ref: 117445
 

About Us

The School of Biomedical Engineering & Imaging Sciences at King’s College London is a world-leading centre for translatable methods of diagnosing and treating disease. Hosted within St Thomas’ Hospital, our facilities include pre-clinical and clinical MRI, PET, SPECT scanners, as well as research ultrasound platforms. The Quantitative Ultrasound Imaging and Interventions (QUIIN) laboratory is developing advanced ultrasound techniques for imaging and therapeutic interventions, spanning from focused brain ultrasound for drug delivery across the blood-brain barrier, to super-resolution ultrasound imaging and multi-transducer ultrasound methods.

About The Role

We are looking for an enthusiastic Postdoctoral Research Associate to develop methods for real-time registration of ultrasound skull imaging to MRI/CT head scans. The project is funded by the Advanced Research + Invention Agency (ARIA), a UK R&D funding agency, whose mission is to unlock scientific and technological breakthroughs that benefit everyone. 

The successful candidate will have a good understanding of image processing, multi-modal image registration, and ultrasound imaging. The post involves the development of software for fast and accurate registration of ultrasound scans of 3D-printed human skulls to MRI/CT head scans. The research associate will develop anthropomorphic head phantoms and algorithms for fast and accurate multi-modal image registration, based on state-of-the-art machine learning approaches. The developed methods will be applied for ultrasound-based navigation in a novel ultrasound engine designed to drive “mosaic neuropharmacology in the brain”. The project’s overall aim is to remotely trigger drug delivery for targeted neuromodulation, through bespoke liposome-microbubble combinations in different parts of the brain. 

The post-holder will lead this exciting ARIA-funded project in the heart of London. The project is highly translational and its results will be used for next generation ultrasound-based navigation in focused ultrasound brain therapies. The project will be based in the Department of Surgical & Interventional Engineering, within the School of Biomedical Engineering and Imaging Sciences, at King’s College London. Ultrasound and MRI/CT experiments will be conducted at St Thomas’ Hospital. The post holder will interact with a multi-national team led by Dr. James Choi at Imperial College London, consisting of interdisciplinary experts from Imperial College London, University of Michigan, and University of Arizona. 

This is a full-time post and you will be offered a fixed-term contract until 31/12/2026.

About You

To be successful in this role, we are looking for candidates to have the following skills and experience: 

Essential criteria

  • PhD in Medical Image Processing, ultrasound/MRI/CT imaging, or a related field* 
  • Experience with multi-modal medical image registration 
  • Computer programming skills (e.g., Matlab, Python, C++) 
  • Strong academic record, evidenced by publications in peer-reviewed journals and presentations in international conferences 
  • Excellent verbal and written communication skills 

Desirable criteria

  • Experience with research ultrasound platforms (e.g., Verasonics) 
  • Experience with MR/CT acquisition sequences 
  • Ability to work independently and in a team 

Downloading a copy of our Job Description 

Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the next page after you click the “Apply” button, above. This document will provide information of what criteria will be assessed at each stage of the recruitment process. 

Further Information

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