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Koziarski Lab - The Hospital for Sick Children | Central Toronto Roselawn, Ontario | Canada | 1 day 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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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 clinically relevant
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on developing advanced machine learning algorithms for monitoring various in vitro cell culture models (2D, 3D, organoids and OOCs), as well as enabling data-driven autonomous experimentation. Developing
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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
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, in partnership with major industry players (Les Éleveurs de porcs du Québec, Olymel, and CDPQ) and MAPAQ. PhD Objectives: This 4-year PhD project aims to develop and validate robust Computer vision
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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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The University of British Columbia (UBC) | Vancouver UBC, British Columbia | Canada | about 11 hours ago
barriers and enablers for cVPP adoption across diverse BC communities (including low-income, vulnerable, and Indigenous groups); (2) develop a technically feasible BC Hydro–to–cVPP coordination framework