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to effective human video perception. What you will do The PhD student is responsible for helping achieve the objectives outlined above. The ideal candidate for this position has a strong background in machine
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multimodal data integration across organismal domains and data modalities, making use of state-of-the-art methodologies such as systems/network analysis, artificial intelligence and machine learning and/or
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, Introduction to Python, making figures using GGplot2 and basic machine learning. These courses are offered to PhD candidates through the PhD Course Centre of the Graduate School of Life Sciences . In
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the next generation of managers as they investigate the opportunities presented by data analytics (machine learning, deep learning, data mining) and new information technologies (platforms, cloud computing
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of everyday life. This project aims to change that by developing AI-driven methods to assess wellbeing through video-based sentiment analyses. As a PhD student, you will develop and refine machine learning
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. This PhD position focuses on the design of novel computer architectures to enable large AI models to run on embedded and edge systems under strict timing, energy, and memory constraints. Current solutions
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adaptation, synthetic data generation, and cross-modal learning to enable models that generalize across defect types and machine configurations. This ensures scalable, accurate defect detection even in low
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parallel, it produces new, high-resolution computer models of the warm Last Interglacial period. Finally, PAST creates new knowledge by synthesising these two approaches through advanced statistics. This PhD
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artificial intelligence, computer science, engineering, mathematics, physics, or a related discipline Demonstratable background in machine learning, information retrieval or natural language processing
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, traditional planning often fails to capture workload variability, uncertainty, and the complex interaction between product features, labor availability, and machine capacity. Your PhD will address