Research Fellow in Deep Learning for Ultrasound Therapy

Employer: University College London
Job location
London, Bloomsbury campus
Job salary
£35,328 - £42,701 per annum, inclusive on London Allowance
Job term
Full Time
Job closing date

Applications are invited for a postdoctoral Research Fellow position to work on applications of deep learning in ultrasound therapy within the Biomedical Ultrasound Group at UCL.

The aim of the project is to develop deep learning models capable of generating treatment plans and predicting treatment outcomes for ultrasound therapies in the brain. In the last few years, clinical trials of different ultrasound therapies have demonstrated the ability of ultrasound to destroy cells through rapid heating for the treatment of cancer, target the delivery of anticancer drugs, stimulate or modulate the excitability of neurons, and temporarily open the blood-brain barrier to allow drugs to be delivered more effectively. However, existing treatment planning techniques based on conventional numerical models can take hours or days to run. Deep learning offers significant potential to disrupt the current state of the art, and deliver tools that can make predictions in real time. A key aspect of the project will be developing tailored deep learning architectures, and analysing model uncertainty and interpretability. The project is part of a larger research program to develop treatment planning software and hardware for stimulating the brain using ultrasound.

The post offers an opportunity to conduct research at an internationally leading university and contribute to the state-of-the-art in ultrasound therapy and deep learning (the open-source k-Wave Toolbox developed by our group is widely used across academia and industry). The appointed person will work in a multidisciplinary team led by Dr Bradley Treeby.

The post is available immediately, and is initially funded for 3 years in the first instance.

Key Requirements

Applicants must have a PhD or about to submit a PhD (or equivalent) with a strong mathematical component (e.g., in applied mathematics, engineering, computer science). Knowledge of the fundamentals of deep learning and inverse problems and experience in developing scientific software in a common coding language (e.g., C/C++, Python, MATLAB). Applicants must have the ability to work collaboratively within a multidisciplinary team of software engineers, physicists, engineers, and clinicians.

Appointment at Grade 7 is dependent upon having been awarded a PhD. Or if about to submit a PhD, the appointment will be at Grade 6B (£30,922 - £32,607 salary, inclusive of London Allowance) with payment at Grade 7 being backdated to the date of final submission of the PhD thesis.

To apply for the role and to access a full job description & person specification Please click here All applications must be submitted via the UCL recruitment website, Job reference 1815479