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Field
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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
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(SOTA) Federated Learning algorithms. This includes running a few pre-processing pipelines. Develop SOTA algorithms in Robustness against data and model poisoning attacks. Develop SOTA algorithms in
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the research areas of Infection Medicine and Microbiology, Immunology, Oncology, Neurosciences, Pharmacology/Cardiology/Vascular Medicine, Imaging Technology and Biomedical Engineering, amongst others. A large
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experimental use of organoid models (provided by a partner institute), including adaptation for biophysical assays and imaging Experimental investigations using atomic force microscopy (AFM), including force