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Field
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: A PhD in Mathematics, Computer Science, Engineering or other Machine Learning-related field. Programming experience in MATLAB, Python, C++ or other relevant language and experience in deep neural
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statistical, machine learning, and artificial intelligence (AI) techniques to analyse 'omics and clinical data, and contributing to the development of biomarkers and predictive models. A critical part of your
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implementing bioinformatics pipelines from raw data, applying a range of advanced statistical, machine learning, and artificial intelligence (AI) techniques to analyse 'omics and clinical data, and contributing
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, green finance, ethical supply chains, and behavioural change. Digital and Technologies: AI and machine learning, cybersecurity, spatial intelligence, robotics, human-computer interaction, and digital
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Area: Computer Science 2. Admission Requirements: Graduates (Licenciatura) in computer engineering or related area, with experience in Machine Learning/Deep Learning methods/techniques. 3. Project
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Koziarski Lab - The Hospital for Sick Children | Central Toronto Roselawn, Ontario | Canada | 3 months ago
program at The Hospital for Sick Children, University of Toronto, and the Vector Institute. Our research group focuses on developing machine learning-based pipelines that leverage generative models and
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to the research program. Job Requirements: Preferably a PhD in Computer Engineering, Computer Science, Electronics Engineering, or equivalent. Independent, highly analytical, proactive, and a team player. Excellent
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development; application or development of computational or statistical methods; data analysis; modeling; statistics and machine learning; scientific simulation; or theoretical astrophysics Effective oral and
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therapeutic discovery and providing commercial growers sustainable methods to meet increasing global food demand. Responsibilities Apply machine learning techniques, statistical modelling, and chemometric
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, computational social science, and/or machine learning applications. Acquisition, processing, and analysis of remote sensing imagery. Proficiency with GIS methods, applications, and visualization. Prior experience