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Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL), particularly in Natural Language Processing (NLP) and Computer Vision (CV) Familiarity with genomic and bioinformatic databases
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, Wallumattagal Campus, North Ryde About the Fellowship The China Strategic Knowledge Initiative at Macquarie University invites applications for a full-time Postdoctoral Research Fellowship commencing in 2027
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opportunities within the company. Responsibilities Develop and implement advanced computational and machine learning strategies, including deep learning, graph-based methods, and probabilistic modeling
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, including but not limited to deep learning, computer vision, computational linguistics, pretraining methods, interpretability, and transfer learning Experience with cognitive science, particularly
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Knowledge Initiative at Macquarie University invites applications for a full-time Postdoctoral Research Fellowship commencing in 2027. This is a12-month, residential position based at Macquarie University in
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leadership, shared responsibility, and a deep commitment to genuine care and respect for our community. Find out more about our vision for a truly inclusive workplace in our Diversity, Inclusion and Belonging
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within the digital twin environment Developing deep learning architectures for time-series forecasting, anomaly detection, and predictive maintenance of the physical asset Designing and training Physics
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 2 months ago
deep learning, with demonstrated application to health or medicine A compelling, independently motivated research vision Strong written and oral communication skills; ability to engage with clinical and
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about working at NTNU and the application process here . About the position The Department of Ocean Operations and Civil Engineering has a vacancy for a Postdoctoral Fellow in Steam Turbines for Ships. We
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algorithms, representation and learning of data and dynamical systems, geometric deep learning, topological and algebraic data analysis, optimization on manifolds, and operator- and PDE-based approaches