MSCA Fellowship Research Assistant in Prompt Gamma Multiplexing

The successful candidate will undertake a PhD on the subject of "Multiplexed Total-Body PET via AI and Prompt-Gamma Enabled Imaging". This is a 3-year full-time position as a doctoral candidate (DC) under the auspices of the Marie Sklodowska-Curie Actions Doctoral Networks (MSCA-DN) programme. The successful candidate will develop novel AI-enabled methodologies to separate individual PET tracer distributions following the simultaneous administration of multiple PET tracers, using vast quantities of rich singles gamma list-mode data including prompt gamma emissions as an additional source of information. This approach could enable the simultaneous imaging of different aspects of disease biology within a single scan. The project will involve Monte Carlo simulations and hands-on experimental studies with a range of phantoms using the TBP scanners at King's College London (KCL) to fully characterise their performance with novel PET radionuclides. During the course of the project, the candidate will undertake 1-month secondments at the University of Bern (UBERN) to work on AI-based image reconstruction, at Eberhard Karls Universität Tübingen (EKUT) to apply the developed methods to new datasets, and with our industrial partner Siemens Healthineers AG (SMS) to implement and evaluate methods that exploit prompt gamma information. In addition, the project may include short-term visits to other PREFERENCE partners for data and software exchange. This will be offered as a full time contract until 31st Jan 2030.

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

• Successfully completed studies in Physics, Biomedical Engineering, Computer Science or similar (MSc degree or equivalent)
• Very good command of the English language
• Good communication skills (a pre-requisite for cooperating in a multi-disciplinary environment)
• Willingness to travel and flexibility
• Appropriate physical condition to work in a radiation protection control area
Desirable criteria
• Prior experience of AI-based methods
• Prior experience with medical imaging data will be of benefit
  
  As part of the PREFERENCE consortium, you will have the opportunity to undertake cutting-edge research in Total-Body PET (TB PET), one of the most exciting developments in molecular imaging in recent years. The consortium brings together 12 leading academic institutions with expertise spanning quantitative PET imaging, image reconstruction, physics, artificial intelligence, and data analysis, alongside industrial partners developing next-generation imaging technologies and multi-centre imaging solutions.
We are seeking an enthusiastic, proactive, and collaborative individual to join Professor Andrew Reader's group within the School of Biomedical Engineering & Imaging Sciences at King's College London. You will become part of a multidisciplinary team of physicists, computer scientists, AI engineers, radiochemists, and biologists, with access to world-leading imaging facilities, advanced computational resources, and cutting-edge PET technologies. Together, we are advancing the future of quantitative and multiplexed total-body PET imaging., We pride ourselves on being inclusive and welcoming. We embrace diversity and want everyone to feel that they belong and are connected to others in our community. We are committed to working with our staff and unions on these and other issues, to continue to support our people and to develop a diverse and inclusive culture at King's. We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the advert. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible.