We are looking for a proactive research software engineer to contribute to the development of artificial intelligence (AI) solutions for the analysis of volumetric computed tomography (CT) medical images of COVID-19 suspected/confirmed patients. This high-paced project takes place within an international consortium called icovid (https://icovid.ai/) led by Icometrix, Belgium. The tools developed at King's by the postholder will be fast-tracked for integration within the CE marked icolung product supported by the collaboration.
The postholder will report to Prof Tom Vercauteren (https://www.kcl.ac.uk/people/tom-vercauteren), the icovid lead at King's. The postholder will primarily be responsible for the development and validation on an innovative deep learning based interactive segmentation software. Our team has previously designed and patented an interactive segmentation algorithm for segmentation which we evaluated for various structures in medical images such as brain lesions (Guotai Wang et al. 2018, 2019). This module will be expanded and adapted for COVID-19 lesions and integrated in the icolung pipeline, enabling clinicians or expert annotators to efficiently amend the automatically-generated segmentations (if deemed necessary) to ensure optimal results in real-world settings with little control on the imaging conditions.
Strong software development skills and a good understanding of medical image computing algorithm, in particular machine learning based segmentation is expected.
About icovid: The icovid project is the continuation of the pro bono icovid initiative, resulting in the AI-based CT analysis software, icolung. The icovid project aims to further improve the software, making it of greater value as the clinical needs evolve, validating it in renowned academic centers and deploying it at large-scale across Europe. icolung is expected to have a significant societal impact by increasing confidence when making a CT diagnosis and providing accurate quantification of disease and prognostic information in patients with suspected COVID-19 disease. The consortium builds further on the existing organic collaboration and contains world-renowned experts of which multiple are part of the Executive Committee of the European Society of Thoracic Imaging.
The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.
GRADE 7 - as above PLUS:
*Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In these circumstances the appointment will be made at Grade 5, spine point 30 with the title of Research Assistant. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6.
This post is subject to Disclosure and Barring Service and Occupational Health clearance.
This advertisement does meet the requirements for a Certificate of Sponsorship under Home Office regulations and therefore the university will be able to offer sponsorship for this role.
This is a full-time fixed term contract for 18 monthsContinue reading
|Title||Research Associate or Research Fellow - Deep Learning for COVID-19 Lesion Segmentation|
|Employer||King's College London|
|Job location||King's College London, Strand, WC2R 2LS London|
|Published||October 6, 2020|
|Application deadline||November 1, 2020|
|Job types||Researcher  |
|Fields||Algorithms,   Medical Imaging,   Artificial Intelligence,   Computing in Mathematics, Natural Science, Engineering and Medicine,   Programming Languages,   Software Engineering,   Machine Learning,   Computer Vision  |