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to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device (SFDI) and also from our custom-built photoplethysmography (PPG) sensor
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(SFDI) and also from our custom-built photoplethysmography (PPG) sensor. Applicant should have experience in time-series processing with appropriate AI models (recurrent networks, LSTM) and experience in
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•Nanofabrication and demonstration of optoelectronic devices (e.g., LEDs, infrared cameras, and gas sensors)•Optical and multiphysics simulations (e.g., Lumerical FDTD, COMSOL)We offer a collaborative and supportive
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of quantum dots, 1D/2D materials, and organics•Nanofabrication and demonstration of optoelectronic devices (e.g., LEDs, infrared cameras, and gas sensors)•Optical and multiphysics simulations (e.g., Lumerical
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of chemoreceptor (CR) genes and other sensor proteins in phytopathogenic bacteria. Biochemical charactherization of CRs and sensor proteins. Functional charactherizations of mutants in the context of plant
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electric machines•Nanomaterials for next-generation electronic and photonic nanodevices•Oxide materials for MEMS piezoelectric and multiferroic sensors/actuators•Solid-state devices such as solar cells
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cytosolic RNA/DNA sensors in cytokine secretion and peripheral/tissue Treg regulation will be examined. In addition, investigating the efficacy of anti-purinergic receptor therapy in vivo is also in progress
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& Environment and Climate Change Canada3. Quantifying Forest Biomass Change with High-Resolution Satellite Sensors•Using L-band SAR, LiDAR and optical satellite observations to monitor biomass
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and implementing innovative solutions at the intersection of sensor data collection, machine learning, and real-time decision-making. Specifically, the candidate will contribute to projects focused
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and training. -Support processing and integration of datasets, including UAV imagery, satellite data, IoT sensor data, and field observations. -Contribute to workflows for AI/ML applications, crop