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backgrounds such as AI, computer vision, computer graphics, machine learning, robotics, wearable technologies, textile engineering, fashion technology, digital fashion, or related areas are encouraged to apply
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the impacts of extreme heat exposure on learning and decision-making, as relevant to mental health. This is a full-time role, based in Central Cambridge. The primary function of this post is to undertake
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explore multimodal learning and unlearning techniques using vision, language, and audio signals to build intelligent systems capable of interpreting and responding to human actions and emotions. This work
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insights for streaming, broadcast, accessibility and media production. Candidate profile Applicants should have a background in machine learning, audio engineering, speech processing or a related discipline
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how machine-learning-based methods can help overcome this bottleneck, opening the door to excited-state simulations at scales and system sizes that are currently out of reach. You will work at the
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of video and low-cost sensor technologies to capture subtle movement patterns, creating a rich dataset for AI-driven analysis. Machine learning, deep learning, computer vision and multimodal AI methods will
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| Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 30.09.2029 Reference no.: 6194 Explore and teach at the University of Vienna, where more than 7,500 academics thrive
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Sciences with this industrial PhD studentship in Physics – fully funded by the University of Exeter and Leonardo UK. We’re looking for a student who has a passion for science, with ambition to learn and
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data analysis would be highly advantageous but is not essential. We value reliability, care in laboratory practice and willingness to learn as much as formal experience. Excellent communication and
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centres, we provide an unparalleled learning environment for its 24,000 students and 13,000 staff. At Cambridge, our mission is to contribute to society through world-class education, learning, and research