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, computer science, computational biology and computational statistics. More information about us, please visit: Department of Mathematics . Project description We seek to recruit a PhD student for the following
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This PhD scholarship is for candidates interested in developing culturally inclusive AI by creating methods and datasets to align large language models with global social and legal norms. This PhD
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research and large and thriving graduate research community. We provide an active and stimulating environment to carry out your doctoral research and have an extensive range of specialist labs and facilities
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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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of biological diversity. You will learn to handle large-scale genomic datasets and become an expert on state-of-the-art bioinformatics methods to analyse them, including command-line work, programming, and data
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semester Application deadline The deadline for the DAAD EPOS scholarship via BIGS-DR is 31 August for the following academic year. For applicants with secured funding, the deadline is 1 May for a start in
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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
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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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of cardiovascular diseases. You will work independently to develop mechanistic models that describe dynamic processes of the microcirculation and analyze large data sets using statistics and deep learning