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machine learning algorithms and techniques to materials science problems, including supervised and unsupervised learning, deep learning, and reinforcement learning; Experience with data preprocessing, model
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model serving frameworks like Triton or vLLM, as well as their cloud-managed equivalents (e.g., Amazon SageMaker, Azure Machine Learning, Vertex AI). Strong understanding of high-performance and AI
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want to develop your career on a collaborative, high-performing team with passionate, generous colleagues who will support you to learn and grow? The UBC Faculty of Medicine is seeking a Development
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, 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 commitment
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program. Analyze and interpret remote sensing datasets (satellite, UAV, and/or LiDAR-derived) relevant to fire, fuels, and landscape-scale research questions. Develop and/or adapt machine learning and deep
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CRC2 & Mitchell Funded Tenure-Track Faculty Positions in Supercomtuping and High-Performance Computi
Queen's University - Electrical and Computer Engineering, Smith Engineering | Kingston Downtown, Ontario | Canada | about 9 hours agoprovided by the Engineering Teaching and Learning Team, the Queen’s Centre for Teaching and Learning, the Department, and Smith Engineering. The Department of Electrical and Computer Engineering has 36 full
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Sciences, the successful candidate will be expected to develop and lead an independent research program in computational oncology, centred on new quantitative and machine-learning methods, including
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minimal supervision in a dynamic and fast-paced environment. Intermediate computer skills required (e.g. Workday, MS Office, MS Teams, Zoom) and willing to learn new computer programs essential to working
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applying machine learning techniques to extract findings from data for pilot studies and research initiatives is also considered an asset. Excellent interpersonal, oral, and written communication
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on investigating, analyzing and writing up projects related to building a program for speech-based monitoring of neurodegeneration using behavioural and neuroimaging datasets combined with machine learning