Post-Doctoral Research Associate in Deep Learning for Surface-to-Volume Alignment of Multi-Modality MRI
Saturday 20th June 2020
Closing Date: 05 July 2020
The Department of Biomedical Engineering, King's College London, seeks a Research Associate to work with Dr Emma C. Robinson on the development of novel Machine Learning and Image Processing for precision registration of multimodality brain scans.
This 3-year post is funded by a Wellcome Trust Collaborative Award shared between King's College London, the FMRIB centre, University of Oxford, and the Donders Institute, Nijmegen. Successful applicants will work under the supervision of PIs from two or more institutions on the grant.
The post is available to be filled as soon as possible, the post-holder would be responsible for:
Exploring optimisation and (deep) learning-based solutions to surface-to-volume brain image registration.
Integrating multimodal imaging sources, including structural, functional and diffusion MRI in order to enhance correspondence across modalities.
Exploring new techniques for precision modelling of cortical organisation to further enhance population-level comparisons of the data.
Applicants will be expected to hold a PhD (or be close to completion) in a relevant numerate/computational domain. A track record in medical image processing and/or machine learning, with strong proficiency in Python, or C/C++ is highly desirable.
This post will be offered on a fixed-term contract for 3 years, or until 31 December 2024
This is a full-time post
The selection process will include a panel interview, a paper review, a presentation.
|Organization||King's College London|
|Title||Post-Doctoral Research Associate in Deep Learning for Surface-to-Volume Alignment of Multi-Modality MRI|