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for scaling new models of care. The course explores how data and AI coordinate people, processes, and technology to support behavior change, precision care pathways, and continuous service improvement. Case
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prototype and validate your research directly in the field. Integration into a dynamic, multidisciplinary team (engineers, computer scientists, animal scientists, veterinarians). Collaborations with
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, in partnership with major industry players (Les Éleveurs de porcs du Québec, Olymel, and CDPQ) and MAPAQ. PhD Objectives: This 4-year PhD project aims to develop and validate robust Computer vision
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not required): Experience with ML-based tools for image-analysis and signal processing, development of ML prediction tools Experience with PyTorch and/or TensorFlow, experience with databases and high
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 6 hours ago
aging, vaccines, molecular biology, and immunology and immunotherapies. Applicants with a PhD or equivalent with an exceptional emerging research program in biomedical data science with application in
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technology development are deeply valued. Applicants must have earned a PhD in a relevant field with a clearly demonstrated record of excellence in research and teaching. We are particularly interested in
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learning technology/AI as a tool to analyze these images and come up with an algorithm to be utilized for early detection of AD/PD when the patient has no visible sign and symptoms. This project is team
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are not limited to: Imaging and diagnostic technologies, including wearables and remote health monitoring; Biomaterials and tissue engineering, including regenerative medicine
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processing, development of ML prediction tools Experience with PyTorch and/or TensorFlow, experience with databases and high-content imaging platforms Familiarity with generative modeling Experience with
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spatial genomics platforms, robotics and advanced cellular imaging, which drive technology development and are housed in the Network Biology Collaborative Centre and the Nikon Centre of Excellence . LTRI