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analytics and implementation of algorithms in care settings along with clinical, business and ethical challenges will be explored. In addition, an overview of the issues within the health industry
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: COMP 250 - Course Title: Introduction to Computer Science Course Number: COMP 251 - Course Title: Algorithms and Data Structures Course Number: COMP 252 - Course Title: Honours Algorithms and Data
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, developing, and implementing innovative machine learning models and algorithms to drive insights from the hEDS*omics multimodal dataset, encompassing clinical, environmental, and multi-omics data. This role
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analytics, and software platform development for industry funded applied research projects. Teamwork with experts in innovative and novel technological solutions on industry challenges. Skills & Abilities
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-based prediction. This includes instrumenting a high-power APS torch with video and acoustic sensors, developing machine learning algorithms for feature extraction, and building predictive models
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Koziarski Lab - The Hospital for Sick Children | Central Toronto Roselawn, Ontario | Canada | about 1 month ago
, reinforcement learning, diffusion, and flow matching, guided by practical considerations of high-throughput chemical synthesis. In addition to algorithm development, the candidate will have the opportunity
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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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: image processing, machine learning, and patient records. Track record of development and implementation of novel machine learning algorithms in the healthcare setting or other spaces. Extensive experience
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disease. In this position, the incumbent will perform the following duties, but is not limited to: 1) High-performance computing workflow for large-scale metabolomics data analysis 2) Development of deep