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Field
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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revolutionized the field of artificial intelligence, leading to remarkable advancements across many applications ranging from image classification to natural language processing. Despite these successes
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involves sending mean, vulgar, or threatening messages or images, posting sensitive, private information and/or lies about another person to make that person look bad, and intentionally excluding someone
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working in interdisciplinary and international teams and have image processing or image analysis skills. In addition, you are able to express yourself confidently both orally and in writing in English. What
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System analysis, prognosis and control Transport processes Image Processing High Performance Computing Financial Mathematics Materials characterization and testing What you bring to the table You have
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clinical use-cases for benchmarking existing state-of-the-art (SOTA) Federated Learning algorithms. This includes running a few pre-processing pipelines. Develop SOTA FL algorithms that tackle data
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Change, Glaciology, Modeling, Imaging, Algorithms and Combinatorial Optimizations. Eligibility to hold scholarship funding: Recipients must be offered and accept admission to a UBC PhD program in
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matter physics, biomedical/material engineering or a related discipline. You have a strong background in data analysis and image processing. You enjoy working in interdisciplinary and international teams
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to study translational aspects of cancer (single-cell sequencing of immune cells, organoid co-cultures, cellular engineering via CRISPR/Cas9 technology, in vivo imaging, advanced animal models of allo-SCT
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closed-loop control. The technology, developed through detailed computer simulations, will be validated with preclinical experiments. The candidate will be part of a multidisciplinary team working towards