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Position: Research Associate in Automated Optical Microscopy
Institution: University College London
Department: Computer Science
Location: London, United Kingdom
Duties: We currently have a Research Associate (Grade 7) vacancy for a physicist or engineer with a background in optical imaging and image analysis to work within a multidisciplinary team based in the Department of Computer Science at UCL. You will be responsible for the development of a cutting-edge optical microscope system utilising fast volumetric imaging and automation techniques for high throughput diagnostic imaging. In addition to the hardware you will develop image reconstruction software and create protocols and metrics to benchmark the quantitative imaging performance against conventional techniques
Requirements: The candidate should have a track record of publications in the areas of either optics, microscopy or bio-imaging. The candidate needs to have programming skills in suitable language such as Python, Matlab, LabVIEW or C++. Knowledge of computer vision algorithms in object detection and instance segmentation will be highly appreciated but not essential
   
Text: Research Associate in Automated Optical Microscopy, - Ref:1723102 Click here to go back to search results Apply Now UCL Department / Division Computer Science Location of position London Grade 7 Hours Full Time Salary (inclusive of London allowance) ?34,635 - ?38,581 per annum Duties and Responsibilities We currently have a Research Associate (Grade 7) vacancy for a physicist or engineer with a background in optical imaging and image analysis to work within a multidisciplinary team based in the Department of Computer Science at UCL. The research is funded by a EPRSC Global Challenges Research Award focused on Fast Accurate and Scalable Malaria Diagnosis using Machine Learning and Robotic Microscopy (FASt-Mal). The project involves an interdisciplinary group of researchers including clinicians, life scientists, computer scientists as well as robotics, digital and global health specialists. More detail can be read at the EPSRC website:( http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/P028608/1 ) You will be responsible for the development of a cutting-edge optical microscope system utilising fast volumetric imaging and automation techniques for high throughput diagnostic imaging. In addition to the hardware you will develop image reconstruction software and create protocols and metrics to benchmark the quantitative imaging performance against conventional techniques. You will apply the system to image a range of patient derived samples and work with experts in clinical diagnosis and machine learning to develop new methods for improved detection of diseases including malaria. The post is funded for 22 months in the first instance. Key Requirements The candidate should have a track record of publications in the areas of either optics, microscopy or bio-imaging. The candidate needs to have programming skills in suitable language such as Python, Matlab, LabVIEW or C++. Knowledge of computer vision algorithms in object detection and instance segmentation will be highly appreciated but not essential. 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. If you have any queries regarding the vacancy or the application process, please contact Delmiro Fernandez-Reyes email: delmiro.fernandez-reyes@ucl.ac.uk UCL Taking Action for Equality Closing Date 25 May 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 the UCL Terms and Conditions related to this job, employee benefits that we offer and further information about UCL . Job description and Person Specification Apply Now
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