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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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University, Polytechnique Montreal, University of Calgary, UBC and The University of Victoria). There are 21 Canadian and international companies in the consortium. CANRIMT 3 is led by Prof. K. Erkorkmaz
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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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network of IoT weather sensors. Assemble, configure, and deploy custom IoT devices in field conditions, including satellite communication modules for remote data transmission. Optimize algorithms for edge
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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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developing machine learning algorithms specifically designed for medical imaging applications. In addition, performs analysis of tissue images of cancer using machine learning methods that have been prototyped
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Science Specialist will: 1) review empirical data and algorithms applied to the price, end-use, fishing effort and layer 3 databases and develop code that imputes missing data to complete gaps in
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reports to the Principal Investigator (Dr. John-Jose Nunez) and will also receive direction and some supervision from the Co-Principal Investigator Prof. Raymond Ng. They will also interact with and receive
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and test field protocols for carbon removal tracking and certification Conduct life cycle assessments (LCA) using real-world deployment and sensor data Engage with community partners, carbon credit