Research Associate/Fellow (Fixed term) (SCI412419)

We are seeking an outstanding researcher to be the main contributor to a pioneering “proof-of-principle” project funded by Precision Imaging Beacon at University of Nottingham.  

We aim to develop and test an AI-augmented pragmatic diagnostic strategy for patients with suspected occult scaphoid fracture (SF), to include MRI scanning at presentation to A&E alongside elicitation of simple clinical signs by non-specialists in the emergency setting. This position offers an opportunity to work at the forefront of this interesting research area. The successful candidate will be working in developing efficient and robust algorithms for carpal bone localisation and bone fracture detection in MRI. She/he will be part of the Intelligent Modelling and Analysis group within School of Computer Science and collaborating closely with colleagues from Medical School and Sir Peter Mansfield Imaging Centre at University of Nottingham.

Applications are invited from highly skilled researchers in Computer Science, Mathematics, Engineering or closely related disciplines. A PhD (or close to completion) in one of these fields is ideal but not essential if you have other desirable skills. In-depth knowledge of image processing, computer vision and particular machine learning/deep learning algorithms are desirable. Strong programming skills in Matlab and Python are essential. Hands on experience using deep convolutional neural networks for object detection/segmentation/classification is a plus.

The successful candidate should be able to work both independently and collaboratively and be able to meet tight deadlines. Good communication skills to work within multidisciplinary teams are crucial. The candidate will be expected to disseminate research results in high-quality journals and top conferences.

This post is available from January 2020 on a fixed-term contract which will end on 5th July 2021. Hours of work are full time (36.25 hours). Job share arrangements may be considered.

Informal enquiries may be addressed to Xin Chen, email: xin.chen@nottingham.ac.uk. Please note that applications sent directly to this email address will not be accepted.

Closing Date: 11 Dec 2019
Category: Research and Teaching (R&T)