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: Machine learning/deep learning model development for biomolecular data analyses and prediction Research Area: Data science and computational chemistry Required Skills: A Ph.D. in relevant field within
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Koziarski Lab - The Hospital for Sick Children | Central Toronto Roselawn, Ontario | Canada | 11 days 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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: 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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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
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Postdoctoral Fellowship in Quantum Navigation Two postdoctoral positions are available immediately in Professor Cory’s laboratory for the development of a quantum navigational device in
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The fellow will be responsible for: Building collaborations with our multidisciplinary team (medical physicists, engineers, computer scientists, nuclear medicine physicians) to develop and implement innovative
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scientists, nuclear medicine physicians) to develop and implement innovative AI algorithms applied to medical images To lead effort on enabling translational and physician-in-the-loop AI solutions for medical
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. Responsibilities include (but not limited to): Lead the development of the NC-ARPES technique (hardware, post-processing algorithm, theory, data interpretation) Propose and perform new TR-ARPES studies of quantum
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Fellow in Artificial Intelligence and Indigenous Knowledge for its research “pod” in Toronto, Canada. Abundant Intelligences conceptualizes, designs, develops, and deploys Artificial Intelligence based
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motivated and skilled postdoctoral fellow to join a project focused on developing statistical models to understand the spatiotemporal distribution of marine mammals in the Arctic. The project will help