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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | 2 months ago
& Medicine. This is an exceptional opportunity for a talented and ambitious researcher to build an independent, high-impact research program at the intersection of machine learning and healthcare
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. Ideal candidates will have demonstrably strong research skills, evidenced by multiple publications in top-tier machine learning or artificial intelligence conferences and/or leading scientific journals
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(e.g. reports, policy documents, gray literature, or citizen science observations), Apply advanced statistical, machine learning, and AI techniques to analyze complex datasets and uncover actionable
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the speed up from using GPUs as well as machine learning techniques, e.g. simulation-based inference. Finally, we will use similar techniques to make a statistical inference of the population of subhaloes by
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insurance, supported by INESC TEC. 2. OBJECTIVES: • Explore machine learning approaches for discovering interpretable and clinically relevant visual representations.; • Validate the proposed methodologies
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framework or knowledge graphs; 2) Uncertainty analysis and risk modelling; 3) Port and maritime operations; 4) Cybersecurity or critical infrastructure protection; and 5) Machine learning and real-time data
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of Computer Science at UNNC is developing research excellence in areas including Machine Learning, Big Data, Visual Analytics, Computational Intelligence, Machine Learning, Software Implementation and Testing, and
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computer vision and vision-language models Experience with ML evaluation metrics and benchmarking Proficiency in Python and deep learning frameworks (e.g., PyTorch) Interest in applied, industry
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towards better understanding what replication can mean for qualitative research. Last but most topically, the theme of replication raises a host of questions in relation to machine learning and artificial
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fluid mechanics, computational geometry, meshing, computational graphics, computational vision, or scientific machine learning in general. Successful candidates will join a community of researchers in