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combined with human support. About the role The Research Scientist in Machine Learning for Wearables will develop predictive deep learning models to assess maternal and partner health and behaviour
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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research team focused on advancing cancer care through cutting-edge computational and AI technologies. We develop innovative approaches that combine deep learning, computer vision, and bioinformatics
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modalities (waveform, DICOM images etc.) - Data manipulation and analysis capability, e.g. machine/deep learning in R/Python or other available tools with an interest in integrating multimodal data from EHRs
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hardware-aware training methodologies optimized for inference with the architecture and collaborate with project partners involved in the experimental demonstrations of various Machine Learning use cases in
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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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, Nutritional Sciences and Women's Health cluster) for REF was rated as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and research
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scale. Posted: 19 June 2025. Closing date: 31 July 2025. Business unit: Faculty of Life Sciences & Medicine. Department: Department of Population Health Sciences. Contact details:Professor Josip Car
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machine learning or AI methods in healthcare research, particularly within digital trials or real-world data studies. Expertise in analysing complex digital health data, including wearable sensor data