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Vision, Robotics, Evolutionary Computation, Deep Reinforcement Learning, and Machine Learning. This should include a proven publication track record. You should also have: Research Associate: A PhD (or
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Associate: A PhD (or equivalent) in an area pertinent to the subject area, i.e. Computer Science, Machine Learning, Robotics. Research Assistant: A Master’s degree (or equivalent) in an area pertinent
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element methods. Additionally, expertise in computational fluid dynamics, solid mechanics and fluid-solid interaction is essential. Knowledge or experience in multi-scale modelling and machine learning
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also have or be close to completing a PhD in any of the following areas as well as the will and commitment to learn relevant topics from the other areas: Statistical and machine learning, mathematical
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vision research. The department fosters interdisciplinary collaboration, addressing real-world challenges through innovative machine learning, data science, and intelligent systems research. About the role
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-quality robotics research in the areas of robot grasping and manipulation, kinematics and mechanisms, sensing, and human-robot interaction. Within CORE, SAIR focuses on multimodal machine learning for human
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-quality robotics research in the areas of robot grasping and manipulation, kinematics and mechanisms, sensing, and human-robot interaction. Within CORE, SAIR focuses on multimodal machine learning for human
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experience in Oxford Nanopore Technologies (ONT) sequencing and bioinformatics A track record of research in microbiome science, metagenomics, whole genome sequencing, big data analysis, machine learning, and
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scientists, and researchers working on medical image analysis, machine learning, and audiology. Our recent work has focused on using deep learning to analyse temporal bone CT scans and brain MRI data in
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area, with content covering robotics and machine learning, and excellent programming skills in Python. You should have research experience in either robotics or machine learning. You should also have