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of Ecology and Evolutionary Biology Campus: St. George (Downtown Toronto) Description: The Department of Ecology and Evolutionary Biology in the Faculty of Arts & Science at the University of Toronto invites
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 8 hours ago
), the Research Associate will work on a project aimed at comparative and evolutionary genomics/phylogenetics of anaerobic protists and associated bacteria. Key Responsibilities Conduct all wet-lab and
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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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of deep learning algorithms. Outstanding programming skills in Python. Extensive experience working on one or more of the following areas: image processing, machine learning, and patient records. Track
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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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learning algorithm for multi-omics integration 3) Maintenance of server / database (Linux environment) 4) Assisting other team members in data analytics 5) Presenting work in at least one conference in
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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
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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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learning models, including their strengths, deficiencies, and strategies for (hyper)parameter optimization. Prior use of Bayesian optimization or other relevant active learning algorithms is preferred