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Position: Research Fellow: Machine Learning for Correlative Imaging from Whole Organ Scale to Cellular Resolution
Institution: University College London
Department: Department of Mechanical Engineering
Location: London, United Kingdom
Duties: UCL is seeking to appoint a Research Fellow to be based at UCL Bloomsbury as part of an international, interdisciplinary project (funded by the Chan Zuckerberg Initiative) to develop a new X-ray tomography imaging modality called Hierarchical Phase-Contrast Tomography (HiP-CT, see mecheng.ucl.ac.uk/HiP-CT), which is capable of imaging whole, intact human organs at 20ìm, zooming down to single cells at 1ìm, without physically sectioning the tissue. You will be part of a multidisciplinary international team of X-ray physicists, computer scientists, medics and computational modellers to develop each stage of HiP-CT. This role will focus on applying machine learning approaches to automate segmentation and correlate HiP-CT upscale to clinical imaging modalities (e.g. MRI) and down-scale to spatial transcriptomics and histological imaging data. The role will require close co-working with researchers, from a range of backgrounds and disciplines, in a collaborative team
Requirements: The post holder will have a PhD and extensive knowledge and expertise in a relevant field, experience with open source machine learning libraries and handling large image datasets are essential, experience with multimodal datasets is desirable. Your expertise should be at a level appropriate for the conduct of research and publishing new knowledge in leading international research journals. The post-holder will need to show a high level of initiative and an ability to work collaboratively and independently. Applicants should have good team-working skills and a strong command of English. Ideally, you would have a proven track record in correlative imaging, maching learning and large data image analysis
   
Text: Research Fellow: Machine Learning for Correlative Imaging from Whole Organ Scale to Cellular Resolution, - Ref:1881362 Click here to go back to search results Apply Now UCL Department / Division Department of Mechanical Engineering Location of position London Grade 7 Hours Full Time Salary (inclusive of London allowance) £36,770 - £44,388 per annum Duties and Responsibilities UCL is seeking to appoint a Research Fellow to be based at UCL Bloomsbury as part of an international, interdisciplinary project (funded by the Chan Zuckerberg Initiative) to develop a new X-ray tomography imaging modality called Hierarchical Phase-Contrast Tomography (HiP-CT, see mecheng.ucl.ac.uk/HiP-CT), which is capable of imaging whole, intact human organs at 20ìm, zooming down to single cells at 1ìm, without physically sectioning the tissue. You will be part of a multidisciplinary international team of X-ray physicists, computer scientists, medics and computational modellers to develop each stage of HiP-CT. This role will focus on applying machine learning approaches to automate segmentation and correlate HiP-CT upscale to clinical imaging modalities (e.g. MRI) and down-scale to spatial transcriptomics and histological imaging data. The role will require close co-working with researchers, from a range of backgrounds and disciplines, in a collaborative team. The successful candidate will join a dynamic international multidisciplinary group of academics, clinicians, beamline scientists, post-docs and PhD students developing and applying synchrotron X-ray and other techniques to study biological systems. The successful candidate will be based at UCL, reporting to Prof. PD Lee, but working as part of a large multi-location team. The post is available from start date till 31st October 2024 in the first instance. Key Requirements The post holder will have a PhD and extensive knowledge and expertise in a relevant field, experience with open source machine learning libraries and handling large image datasets are essential, experience with multimodal datasets is desirable. Your expertise should be at a level appropriate for the conduct of research and publishing new knowledge in leading international research journals. The post-holder will need to show a high level of initiative and an ability to work collaboratively and independently. Applicants should have good team-working skills and a strong command of English. Ideally, you would have a proven track record in correlative imaging, maching learning and large data image analysis. Further Details A job description and person specification can be accessed at the bottom of the page. To apply for the vacancy please click on the Apply Now button below. If you have any queries regarding the application process, please contact Prof Peter Lee on Peter.lee@ucl.ac.uk. HR enquiries about the role may be sent to mecheng.hr@ucl.ac.uk. UCL Taking Action for Equality Closing Date 31 Jan 2022 Latest time for the submission of applications 23.59 Interview date TBC 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 and Person specification Apply Now
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