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, integrating and interpreting them across modalities remains a fundamental challenge. The successful candidate will develop computational and machine-learning frameworks for multimodal neuroscience data
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machine learning with single-cell genomics, spatial omics, and systems biology, supported by strong collaborations across UBC and internationally. Project Recent advances in single-cell and spatial omics
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statistical and machine-learning methods to multi-modal data (omics, imaging, GHGs). Generate figures, tables, and summaries for manuscripts and reports. Apply machine-learning methods to multi-modal datasets
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https://engineering.ok.ubc.ca/ | Northern British Columbia Fort Nelson, British Columbia | Canada | about 16 hours ago
to the development, growth, and leadership of the Computer Engineering Program in the School of Engineering. The program integrates foundational and applied courses in engineering, with hands-on learning and immersive
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Primary Purpose: To provide leadership, vision and direction for the Clinical Learning Resource Centre. The Associate Director, Clinical Learning Resource Centres, oversees the development and
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, Computer Science, Computer Information Systems, Data Science, Environmental Science, Geology, and General Science which allow students to prepare for a variety of exciting careers in science and technology
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experimental design. Proficiency with machine vision and deep learning techniques, including image segmentation, landmark placement and metric learning, for the automation of phenotypic analysis of large image
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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow in Machine Learning for Genomics, Transcriptomics, and Bioinformatics Department Bashashati Laboratory | School
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program and facility. The successful candidate will add to this expertise and help build a new intersection of neuroscience and artificial intelligence. Modern machine learning and AI techniques now enable
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of the fundamental theory of deep learning along with significant experience in the development of software applications that employ neural network and deep learning approaches to computer vision, natural