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Python and deep learning frameworks (e.g., PyTorch) Interest in applied, industry-collaborative research Where to apply Website https://www.timeshighereducation.com/unijobs/listing/413018/research-fellow
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learning techniques pertaining to computational electromagnetics. If the successful candidate has not yet been awarded their PhD, appointment will be made as a Research Assistant (Grade 6B). Payment at Grade
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Requirements: Candidates should hold a PhD in civil engineering, computer science, electrical/computer engineering, robotics, or a related field. Experience in computer vision, deep learning, 3D reconstruction
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vision and deep learning methods relevant to imaging, together with programming experience using modern scientific computing tools such as Python and PyTorch or TensorFlow. The successful candidate will
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MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA | North Ryde, New South Wales | Australia | about 1 month ago
CV (including a list of two referees), a statement of research interests and achievements. Essential A PhD in plant ecology, functional ecology, ecophysiology, environmental biology, or a closely
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verbal, written communication skills In-depth knowledge of deep learning, specifically VLM models, computer vision techniques (e.g., open vocabulary object detection, model distillation, VQA, test-time
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achievements. Essential A PhD in plant ecology, functional ecology, ecophysiology, environmental biology, or a closely related discipline (awarded or under examination). Current work rights in Australia
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We are seeking a Research Fellow - Data Science professional with strong expertise in machine learning, deep learning and high-frequency physiological signal analysis. This is a unique opportunity to
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Learning. Experience with the deep learning ecosystem and high-performance computing infrastructures. Experience designing and conducting experiments with human participants is a strong plus. Experience in
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below: Essential: A PhD in Mechanical Engineering or a related field. Strong experience in computational mechanics and simulation tools (e.g., COMSOL, ANSYS, Abaqus). Experience in thermo-mechanical