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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | 3 months ago
sustainable development. Collaborations with Mathematics and Computer Science The post-doc will also affiliate with Lund's Centre for Mathematical Sciences, renowned for research in machine learning
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: Machine learning/deep learning model development for biomolecular data analyses and prediction Research Area: Data science and computational chemistry Required Skills: A Ph.D. in relevant field within
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contribute to the collaborative TQT research community. Principal Investigator: Na Young Kim Project Name: Solid-state analog Optimization Solver and Quantum Machine Learning (Theory) Research Area
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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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-based prediction. This includes instrumenting a high-power APS torch with video and acoustic sensors, developing machine learning algorithms for feature extraction, and building predictive models
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Python or R and web development to create software, process genomic data, and implement machine learning solutions that assist clinicians in advancing cancer diagnosis and classification. REPORTS TO Dean
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Learning Course Description: Machine Learning applications are increasingly utilized to make crucial decisions in many sectors of our economy and society. These include, but are not limited to, healthcare
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a variety of learning needs General office conditions; sitting at a desk or computer for extended periods of time The salary for the above position is determined by the Collective Agreement with
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REDCap Basic level of computer programming in any language, interest in learning more (e.g., MATLAB) Proficiency with computer programs, including Microsoft Office, Adobe Acrobat, etc. Experience with
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Technology Services department handles all software and hardware needs, as well as technological and networking issues for both employees and students who rely heavily on computer systems across our campuses. Technical