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involves designing and developing solid-state lithium coin cells for powering sensors and actuators in smart wearables, in collaboration with researchers at the University of Alberta. Responsibilities
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machine learning computer models (i.e. algorithms) for medical imaging, bioinformatics (i.e genomics data including single cell and spatial omics) and drug development applications. Performs analysis
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engagement, and educational activities to explore how modern information and communication technologies (e.g. mobile and web-based applications, sensors, wearables, AI/ML etc.) can improve health care. Digital
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of recurring processes. Respond to consulting requests requiring expertise in statistical methodologies and procedures. Provide statistical contributions to data mining operations and algorithm development
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involving project partners including a semi-industrial foundry; Interacts with a team of graduate students and postdocs to investigate qubit properties and demonstrate novel algorithms with support from
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analytics, search algorithms and reporting tools to document knowledge. - Proven knowledge of stakeholder and team communication/interaction, community engagement, knowledge dissemination, and knowledge
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foundry; Interacts with a team of graduate students and postdocs to investigate qubit properties and demonstrate novel algorithms with support from theory partners; Contributes to the preparation and
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of developing algorithms that are both technically robust and clinically relevant, ensuring that these innovations can be integrated seamlessly into existing imaging systems and workflows. Collaborating with
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applications across a wide range of imaging and video processing fields beyond medical imaging. The Research Associate will be at the forefront of developing algorithms that are both technically robust and
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and conferences. Proven experience in design and implementation of deep learning algorithms. Outstanding programming skills in Python. Extensive experience working on one or more of the following areas