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must have a research program with a strong record of peer-reviewed publication using advanced computational methods (such as computational modeling, machine learning, AI, or algorithm development
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Nature Careers | Government of Canada Ottawa and Gatineau offices, Ontario | Canada | about 2 months ago
of large libraries of compounds (e.g. those designed and generated through automated synthesis, computer-based design, and machine learning) and supports users by providing full-time professional staff and a
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existing SC analysis tool, by integrating machine learning and benchmarking components, thus helping evolve it into a market-ready solution capable of real-time threat intelligence and adaptive vulnerability
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intelligence (AI)-assisted image analysis for bioinformatics and medicine. The project is highly interdisciplinary, involving areas of microfluidics, fluidic mechanics, biomedical imaging, and machine learning
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cloning, managing repositories, branching, and implementing collaborative and reproducible data analysis workflows. Experience in applying machine learning or AI approaches to genomics data (e.g. BLUP
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research experience, preferably in programming languages, compilers, applied mathematics, and optimization techniques a strong background in compiler, code generation, and machine learning would be
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and build upon the mathematical foundations for predictive science, data science, machine learning, and (in particular) physics-based modeling using state-of-the-art computing platforms. The Oden
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analysis Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within an experimental team, with direct availability of experimental
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analysis Background in biomedicine and digital pathology What we offer Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within
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experience in AI teaching We understand AI very broadly – and adequate experience would include most topics in modern statistics and topics like Bayesian Machine Learning and Simulation Based Inference (a past