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reproducible analysis workflows Familiarity with computational models of vision and machine learning methods (for example CNNs, deep generative models, encoding models) is preferred but not required Ability
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engineering not commonly found in scientific collaborations. The projects may require the creation of AI/ML solutions using the latest deep learning libraries trained on state-of-the-art hardware. Projects may
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learning. A record of contributing to building and maintaining effective and productive links locally and nationally with the discipline, profession and wider community. Tasmanian Working with Vulnerable
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: Required: • MSc (or equivalent) in: Computer Science, Cybersecurity, Machine Learning, or related field • Strong background in: machine learning / deep learning, mathematics (probability, linear algebra
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appointed as Deputy Head of discipline to provide strategic leadership for Learning & Teaching or Research & Scholarship. About You You are an inclusive academic leader who brings deep disciplinary expertise
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biologically-inspired deep learning and AI models (NeuroAI). The computational models we work with include vision deep learning models (including topographical, recurrent, or developmentally inspired models
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experience in machine learning and artificial intelligence who can teach in areas relevant to AI including machine learning, deep learning, natural language processing, reinforcement learning, robotics and
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to recruit a research assistant to work on the intersection of compilers and deep learning. Many companies, such as Google, Facebook, and Amazon are building new specialized programming frameworks. This is
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-based techniques (e.g., deep neural networks) will be used to automatically learn the system dynamics and the modelling errors, as well as to obtain an automatic tuning of the cost parameters/constraints
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Austrian Academy of Sciences, the Johann Radon Institute for Computational and Applied Mathematics (RICAM) | Austria | 20 days ago
, Approximation Theory, Machine Learning, Inverse Problems and Regularization Theory. Proficiency in programming with a strong preference for Python and deep learning frameworks such as PyTorch is highly desirable