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Field
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develop new deep learning algorithms for spatio-temporal medical image analysis with particular focus on learning from limited labelled data. General information about the position. The position is a fixed
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magnetic resonance imaging (fMRI) and/or neurophysiological data Development and programming of behavioral and cognitive tasks; animal training and testing Planning, preparation, and participation in
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three references and their contact information A link to GitHub repos for relevant code (optional) Starting salaries will vary depending upon the qualifications and experience of the selected candidate
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are developing a groundbreaking technique based on autofluorescence (AF) imaging and Raman spectroscopy for detection of positive lymph nodes during breast cancer surgery. The instrument will allow surgeons
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of what microscopes can achieve. You will create and apply sophisticated algorithms, physics-based simulations, and machine learning models to process complex data from our cutting-edge imaging systems
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various themes, BC Cancer supports ground breaking cancer research and personalized care approaches through world-class facilities and platforms including genomics, bioinformatics, imaging, drug development
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opportunity to undertake the characterisation of cancer cells and tissue using GHz acoustic imaging and characterisation techniques. A key aspect of your role will be to use and develop opto-acoustic
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Support”, through analysis of MR Diffusion Weighted Imaging and MR Spectroscopy and leading other members of the wider team Specific aims of the project To prospectively evaluate non-invasive pre-surgical
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for imaging Apply for this job See advertisement About the position Position as PhD Research Fellow in machine learning available at Department for Informatics with the research group Digital Signal Processing
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and complex environments, based on partial system views. Implement a reference prototype of the developed solution. Experimentally evaluate the proposed solution by comparing it to the state of the art