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to identify new drug candidates and therapeutic targets. As a Research Assistant, you will contribute at the intersection of bioinformatics, machine learning, and natural product drug discovery by applying AI
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learning, offers powerful solutions to automate these tasks and provide reliable real-time information. This doctoral project is part of a 5-year research chair on Computer vision applied to the swine sector
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University of Montreal-CHU Sainte Justine Children's Hospital Research Center | Canada | about 2 months ago
-Language Pathology, Neuroscience, Psychology, Cognitive Science, Biomedical Sciences, Biomedical Engineering, or related field.-Experience with machine learning (preferably RL) and applications in health
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engineering, electrical engineering, data science, or a related field. Skills in embedded systems development, electronics, or IoT (C/C++, Python, Arduino/ESP32, etc.) OR in machine learning and sensor data
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at the University. At UBC, we believe that attracting and sustaining a diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff and students. Our
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experience in optimization, machine learning, control systems, or robotics is desirable. No other specific qualifications beyond and a willingness to learn within an interdisciplinary team. If you have any
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spatial omics datasets. The position will also contribute to multi-modal data integration efforts that combine imaging, genomics, and machine learning approaches. Key Responsibilities Data Processing
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rapid and significant shifts in power consumption, next-generation high-performance computing (HPC) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs
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eligible for an exception to this work arrangement. Alternative work arrangements may also be considered to accommodate candidates as required. To learn more about these options, please contact the hiring
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student to start in September 2025 (preferably) or January 2026 to study aspects of sensory physiology and learning in the context of pollination ecology. Using honey bees and other arthropods, our