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Field
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mismatch remains a key issue for speech and language technologies. Especially for speech technology the variability of input data is large and recordings can occur in highly complex acoustic and linguistic
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The project: The deployment of generative AI—particularly Large Language Models (LLMs) based on transformer architectures—in industrial settings poses several critical challenges. Ensuring reliable
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., StableDiffusion) and large language models (LLMs) based on the transformer architecture [6] (e.g., ChatGPT). In general, the above generative models need considerable amount of computational resources in terms
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power systems. You will join a large group of postgraduate students in the Faculty of Engineering, working on many aspects of solar energy and zero carbon technologies. The team of potential PhD
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power systems. You will join a large group of postgraduate students in the Faculty of Engineering, working on many aspects of solar energy and zero carbon technologies. The team of potential PhD
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health datasets. Ageing is usually quantified as a measurement of the time elapsed since birth. This cannot explain the large variations in ageing trajectories between older people of similar age
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that handle large network sizes and additional information – such as fine-grained temporal information for email traffic or additional neighbourhood structures – are essential. A key challenge in modelling
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, manipulate large datasets, visualise data and perform numerical and statistical analysis is a requirement. Experience in handling 'big data', machine learning and working in distributed teams, is useful
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position is part of a large-scale research project around immune response in neurodegenerative disease. The PhD student will be part of a data science team working on data analysis and experimental design as
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-on experiments & development and opportunities for travel to international facilities. This project is supported by the large investment of a URKI Future Leaders Fellowship to identify, synthesise and explore new