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Field
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Computational Sciences to lead a program in immune repertoire profiling, decoding, and analysis. The individual will manage multiple individuals at various ranks, providing support a) sample selection and study
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-resource settings. This project aims to achieve several objectives, including the development of a new AI-algorithm and a paired dataset for comparing how different imaging techniques influence
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understanding of HLA donor search algorithms and other non-HLA factors, such as ABO, age and CMV status. Analyze donor searches and apply current donor selection algorithms and strategies. Responsible
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of Biomedical Engineering, please visit https://www.bme.ubc.ca/ . HuMBL, a research lab within the SBME, specializes specifically in wearable sensor technologies and algorithm-driven health analytics to enhance
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combining multiple ML models have been explored to optimise predictions, enabling algorithms to collaborate and achieve better results. Ensemble methods, in particular, have demonstrated superior performance
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, Hugging Face etc., in applied problem-solving contexts. Understanding of machine learning algorithms (gradient descent, random forests, etc.) and deep neural network architectures (ResNet and Transformers
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university. Strong communication skills in the English language Passionate in teaching electrical/computer engineering concepts and skills to the students. Proficient in multiple programming languages
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(Required) Experience creating and utilizing statistical algorithms and conducting power calculations to determine sample size to answer complex research questions. (Required) Demonstrated experience working
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bioinformatics research coupled with wet-lab investigations, working in the areas of network biology, data-driven hierarchical modeling, and machine learning applied to biomedicine. We also support multiple open
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the design and development of multiple projects using state-of-the-art AI models, algorithms, statistical models, and other programs designed to improve the public sector. Work with large untapped data