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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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: Department of Mathematics and Statistics Position Summary : Optimize ML RNN/CNN models on sensor data with healthcare applications. Help interdisciplinary researchers to publish clean codes in public
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. Key Responsibilities Lead AI/ML algorithm development for predicting plant water and nutrient uptake under varying environmental and growth conditions. Analyze multi-source data, including aerial and
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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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data sources such as UK Biobank and eventually come up with algorithm useable for the early detection of Alzheimer’s disease (AD) and Parkinson’s disease (PD). Nature of Work: In this project, we will
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candidate will support experimental research focused on the synthesis and characterization of photo-activated semiconductor materials. Responsibilities include developing and testing UV-activated gas sensor
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characterization of photo-activated semiconductor materials. Responsibilities include developing and testing UV-activated gas sensor prototypes, conducting laboratory and field evaluations, and analyzing
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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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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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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