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more than 2000 individuals followed up for more than 10 years) and as the Australian Dementia Network (ADNeT). The goal is to develop quantification pipelines using traditional imaging algorithms and/or deep
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Apply now Job no:523884 Work type:full time Location:Sydney, NSW Categories:Post Doctoral Research Associate The Opportunity We are looking for machine/deep learning expert to join our team that is
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to be a global leader in dual-sector learning and research by 2028. Join us on the journey and help us achieve our strategic drives embedded in our Strategic Plan 2022-2028: Start well, finish
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of data analysis techniques (including machine learning) and process-based algorithms to diagnose and interpret high-frequency hydraulic data for the purpose of providing actionable information. Analysis
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. The research fellow will program and develop generative artificial intelligence and deep learning systems, including working with state-of-the-art transformer and diffusion models. This experience will be
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. This position will involve the development of data analysis techniques (including machine learning) and process-based algorithms to diagnose and interpret high-frequency hydraulic data for the purpose
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to train human-robot interaction policies in simulation. These models will be constructed by identifying and integrating known human behavioural biases into deep learning models fit to human data. Working
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deep learning, and proficiency in using machine learning or deep learning libraries such as scikit-learn, PyTorch, Tensorflow Advanced skills in computer programming for data manipulation and analysis
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You Completion or near completion of a PhD in the computer science or relevant field. Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and familiarity with Multimodal Foundation
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, or similar. Required: Demonstrated experience in machine learning, such as deep learning for image processes, deep learning for natural language processing, or interpretable machine learning (for machine