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Position: Research Fellow in Medical Image Computing: CT Image Analysis
Institution: University College London
Department: UCL Department of Computer Science
Location: London, United Kingdom
Duties: This post will be focused on developing computational methods to: analyse low dose lung CT images and identify features of early lung fibrosis, align longitudinal CT images to quantify fibrosis progression on a lobar basis and use unsupervised learning techniques to identify distinct disease phenotypes that link to patient genetics and blood biomarkers
Requirements: Applicants must have, or expect to obtain, a PhD in a relevant discipline. They should be able to demonstrate a good publication record in peer reviewed publications. Experience is essential in one or more of the following areas: computational imaging, machine learning, medical image analysis and image registration. A demonstrable ability in programming skills is essential
   
Text: Research Fellow in Medical Image Computing: CT Image Analysis, - Ref:1757470 Click here to go back to search results Apply Now UCL Department / Division UCL Department of Computer Science Specific unit / Sub department Centre for Medical Imaging Computing (CMIC) Location of position London Grade 7 Hours Full Time Salary (inclusive of London allowance) ?35,328 - ?42,701 per annum Duties and Responsibilities The Centre for Medical Image Computing (CMIC: http://cmic.cs.ucl.ac.uk ), and Dept. of Computer Science (UCL-CS: http://www.cs.ucl.ac.uk ) at University College London (UCL: http://www.ucl.ac.uk ) is offering a new post-doctoral research position to work on low dose lung CT image analysis for the identification of early lung cancer and lung fibrosis. The new post is allied to one of the largest lung cancer screening studies performed to date in the world, which will screen 25,000 patients annually for three years with low dose lung CT. The project will run in collaboration with the Respiratory department at University College London. The project aims to develop novel algorithms, such as deep learning, to exploit a large data set to identify early lung fibrosis and lung cancer. This post will be focused on developing computational methods to i) analyse low dose lung CT images and identify features of early lung fibrosis, ii) align longitudinal CT images to quantify fibrosis progression on a lobar basis and iii) use unsupervised learning techniques to identify distinct disease phenotypes that link to patient genetics and blood biomarkers. The successful candidate will work closely both with post-doctoral researchers within the group and clinicians at UCLH. This is an exciting opportunity to develop state-of-the-art imaging and machine learning methods and apply them directly on clinical data to address open questions in medical imaging and fibrosis/cancer detection. This project aims to develop novel algorithms to detect features of early lung fibrosis and lung cancer on low-dose CT imaging in a lung cancer screening population. Supervised machine learning techniques will be used to identify phenotypes of early fibrosis that are likely to become progressive disease on longitudinal CT imaging. UCL is among the top-ten world-wide research institutions and has particular strengths in Biomedicine and Engineering. CMIC combines methodological researchers from the Departments of CS and Medical Physics & Bioengineering with biomedical and clinical groups in UCL?s Medical Faculties. The interface of these areas is a unique and exciting place to do cutting-edge research. This post is funded for 2 years in the first instance. Key Requirements Applicants must have, or expect to obtain, a PhD in a relevant discipline. They should be able to demonstrate a good publication record in peer reviewed publications. Experience is essential in one or more of the following areas: computational imaging, machine learning, medical image analysis and image registration. A demonstrable ability in programming skills is essential. Appointment at Grade 7 is dependent upon having been awarded a PhD; if this is not the case, initial appointment will be at Research Assistant Grade 6B (salary ?30,922 - ?32,607 per annum) with payment at Grade 7 being backdated to the date of final submission of the PhD thesis'. Further Details A job description and person specification can be accessed at the bottom of this page. To apply for the vacancy please click on the ?Apply Now? button below. For further details and informal enquiries please contact Dr Joseph Jacob (j.jacob @ucl.ac.uk). UCL Taking Action for Equality Closing Date 29 Nov 2018 Latest time for the submission of applications 23:59 Interview date TBC Our department holds an Athena SWAN Silver award, in recognition of our commitment and demonstrable impact in advancing gender equality. This appointment is subject to UCL Terms and Conditions of Service for Research and Support Staff. Please use these links to find out more about UCL working life including the benefits we offer and UCL Terms and Conditions related to this job. Job Description & Person Specification Apply Now
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