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Field
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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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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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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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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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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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Editing of 2D and panoramic images and 3D processing Ensure the processing of photographed objects, in accordance with the defined technical specifications 4. Applicable Legislation and Regulations: Law No
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datasets (e.g., images, surveys, statistical and sensor data). Familiarity with geostatistical, GDAL, Python, PostGIS/PostgresSQL, Machine Learning, AI, Internet of Things and Remote Sensing datasets is
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the Research Fellow Statute (EBI), by the Norms for Grant Assignment and Management within R&D Projects, by the Code of Administrative Procedure (CPA), all in their current wording, and by other applicable
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English communication skills, the ability to write code using Python or MATLAB, the desire and ability to work as part of a multicultural team, and a demonstrated ability for creating intellectual value
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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