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required. Programming skills are not necessary, but experience in genomic research and a broad knowledge of methods and algorithms behind genomic resources is required (e.g. next-generation sequencing
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candidates with computational tools and machine learning algorithms, and elucidating structure-property relationships of emerging molecules, polymers, solid-state materials, formulations, etc. Tasks include
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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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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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Koziarski Lab - The Hospital for Sick Children | Central Toronto Roselawn, Ontario | Canada | about 2 months 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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design of the basic vertebrate form. With a little evolutionary reworking, this basic form has produced a staggering variety of life forms on this planet. Through lectures, labs, and drawing analyses
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media, newsletters, and event promotion. Ability to research and adapt to evolving social media trends, algorithms, and digital marketing techniques. Experience creating and managing content calendars and
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and conferences. Proven experience in design and implementation of deep learning algorithms. Outstanding programming skills in Python. Extensive experience working on one or more of the following areas
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Systems), 226 (Genes to Genomics), 228 (An Introduction to Ecology and Ecosystems, T1), 301 (Critical Issues in Biology, T1), 302 (Evolutionary Processes, T2), 316 (Molecular Genetics of Eukaryotes, T1