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organ-on-a-chip (OOC) models, colony picking and bioprinting). The ideal candidate should have strong expertise performing machine learning (ML), computational biology with the capability and/or
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organ-on-a-chip (OOC) models, colony picking and bioprinting). The ideal candidate should have strong expertise performing machine learning (ML), computational biology with the capability and/or
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Academic Job Category Faculty Non Bargaining Job Title Research Associate in Machine Learning Department Research | Gsponer | Michael Smith Laboratories | Faculty of Science (Joerg Gsponer) Posting
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title: CSC2515HS - Introduction to Machine Learning Please note, this position is a 0.5 FCE appointment. Course description: Machine learning (ML) is a set of techniques that allow computers to learn
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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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application of natural language processing (NLP) and other machine learning methods, including training and deploying large language models (LLMs) for extracting data from electronic health records (EHRs
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 4 hours ago
development and accreditation. Responsibilities: The successful candidate will teach six undergraduate courses per year in the Computer Engineering curriculum. Courses may include: Computer Architecture
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) and dynamic spread models for invasive forest and agricultural pests, integrating multi-source ecological data using machine learning and statistical approaches. Develop and validate phenological models
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emerging technologies such as machine learning and artificial intelligence. In addition, the ideal applicant will have excellent communication skills and have demonstrated capacity and aptitude for effective
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 14 hours ago
program development and evaluation. Must have strong computer skills, including the use of Microsoft Word, Excel, PowerPoint, Adobe Acrobat, and email software, as well as an ability to adapt to and learn