Proton therapy has emerged as a powerful cancer treatment technique due to its superior tumour‑targeting capabilities. Both conventional and ultra‑high dose‑rate proton therapies demand advanced imaging technologies to enable accurate in‑vivo three‑dimensional dose verification and treatment delivery assessment. A promising imaging technology is proton–acoustics, relying on detecting acoustic waves generated by proton–tissue interaction for real‑time in‑vivo 3D proton beam imaging and dosimetry. However, proton‑acoustic waves are weak, noisy and broadband. To address these challenges, this project will employ deep‑learning techniques for signal denoising and 3D dose reconstruction.
The project is in close collaboration with the National Physical Laboratory and the Institute of Cancer Research, and benefits from the scientific environment and resources provided by the Centre for Vision, Speech and Signal Processing (CVSSP) and the Institute for People‑Centred AI at the University of Surrey.
Applicants
We are looking for applicants with a degree in Computer Science, Mathematics, Physics, or Engineering. Prior experience in AI is necessary. Prior experience in tomographic imaging and medical physics would be advantageous but is not required.
Essential Criteria
* A First Class undergraduate degree or MSc with Distinction (or equivalent overseas qualification) in mathematics, computer science, physics or engineering.
* Excellent mathematical, analytic, and programming skills.
* Prior experience in AI.
* Prior experience in tomographic imaging would be advantageous.
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