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strong background in machine learning, computer vision, or data-driven modeling. You have extensive experience in the development and implementation of AI and machine learning algorithms, ideally with
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position, available until December 2027. Flexible work arrangements can be negotiated with the right candidate. Be part of the Australian Institute for Machine Learning – the largest computer vision and
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(completed or near completion) in Computer Science, Computer Vision, NLP, Machine Learning, Computer Graphics/Animation, HCI, or a related field. Strong background in deep generative modelling (diffusion
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. DVXplorer), and tactile/force sensors. Strong background in computer vision and deep learning, with practical implementation experience. Proficiency in programming with C++ and Python, including use of ROS
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Institute for Machine Learning – the largest computer vision and machine learning research group in Australia – and contribute to world-leading research projects at the Centre for Augmented Reasoning
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students. Qualifications: Required: PhD in Computer Science, AI, Data Science, Statistics, or related. Strong skills in machine learning and deep learning, with a fundamental understanding of LLMs
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-based cameras (e.g. DVXplorer), and tactile/force sensors. 3. Strong background in computer vision and deep learning, with practical implementation experience. 4. Proficiency in programming with
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skills for this position are: o Good knowledge of the technological challenges of agricultural/viticultural robotics. o Proven skills in: vision-based robot modeling and control; computer vision and
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. Essential qualifications: PhD in Computer Science, Robotics, Machine Learning, or related fields. Programming skills in Python/C++ and experience with ML frameworks (e.g. PyTorch, TensorFlow, JAX). Strong
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 21 hours ago
focused on the development and validation of AI- and machine learning–based methodologies for the analysis and interpretation of complex biomedical data. Specific research areas include: Diagnosis and