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Position: Research Associate/Senior Research Associate in Machine Learning for Automated Optical Medical Microscopy
Institution: University College London
Department: Computer Science
Location: London, United Kingdom
Duties: We are seeking to recruit a Research Associate (Grade 7) or Senior Research Associate (Grade 8) to lead the machine learning components of the Fast-Mal team. The core task will be to develop, deploy and use deep learning and machine learning algorithms for the detection and segmentation of blood cells, white blood cell and parasites in a large database of microscopy images
Requirements: The candidate should have a track record of publications in top-level conferences and journals in the areas of either medical imaging, automated microscopy, computer vision, artificial intelligence or machine learning. The candidate should have demonstrably used machine learning in her/his research. The candidate needs to have strong programming skills in Python, Matlab or C++ handling large datasets. The candidate should have demonstrable skills in deep learning libraries such as Tensorflow, PyTorch or Keras applied to large datasets. Knowledge of computer vision algorithms in object detection and instance segmentation will be desirable
   
Text: Research Associate/Senior Research Associate in Machine Learning for Automated Optical Medical Microscopy, - Ref:1723103 Click here to go back to search results Apply Now UCL Department / Division Computer Science Location of position London Grades 7-8 Hours Full Time Salary (inclusive of London allowance) Grade 7: ?34,635 - ?41,864 per annum, Grade 8: ?43,023 - ?46,716 per annum Duties and Responsibilities The research is based at UCL Department of Computer Science and it is funded by an EPRSC Global Challenges Research Award focused on Fast Accurate and Scalable Malaria Diagnosis using Machine Learning and Robotic Microscopy (Fast-Mal). We are seeking to recruit a Research Associate (Grade 7) or Senior Research Associate (Grade 8) to lead the machine learning components of the Fast-Mal team. The core task will be to develop, deploy and use deep learning and machine learning algorithms for the detection and segmentation of blood cells, white blood cell and parasites in a large database of microscopy images. The post is funded for 26 months in the first instance. Key Requirements The candidate should have a track record of publications in top-level conferences and journals in the areas of either medical imaging, automated microscopy, computer vision, artificial intelligence or machine learning. The candidate should have demonstrably used machine learning in her/his research. The candidate needs to have strong programming skills in Python, Matlab or C++ handling large datasets. The candidate should have demonstrable skills in deep learning libraries such as Tensorflow, PyTorch or Keras applied to large datasets. Knowledge of computer vision algorithms in object detection and instance segmentation will be desirable. 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 Dr. Delmiro Fernandez-Reyes via 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 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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