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the most important. Our focal subjects: sustainable aerospace, big data and artificial intelligence, bio-inspired engineering and smart instruments and systems. Working at the faculty means working together
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Abilities: Bachelor's degree and 12+ years, or Master's and 9+ years, or PhD and 4+ years post-PhD. Expertise with foundation models, large vision-language models, or large-scale deep learning training
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are predominately held in English. Full-time / part-time part-time (study alongside work) full-time Programme duration 8 semesters Beginning Only for doctoral programmes: any time Additional information on beginning
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. Our focal subjects: sustainable aerospace, big data and artificial intelligence, bio-inspired engineering and smart instruments and systems. Working at the faculty means working together. With partners
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partners (schools, public and private sectors) and engage with the analysis of the collected data. This main goal of this particular PhD fellowship is to explore how humans interact with the automatically
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leading interdisciplinary hub that advances foundational research, responsible innovation, robust governance and broad capacity building. This PhD fellowship is associated with the second cluster
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escape. To monitor these mutations and to understand their impact, it is crucial to analyse genomic big data efficiently and accurately. Genomes are studied through genome sequencing, but
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, such as virulence, drug response and vaccine escape. To monitor these mutations and to understand their impact, it is crucial to analyse genomic big data efficiently and accurately. Genomes are studied
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for a: PhD Candidate in Emotionally and Socially Aware Natural Language Processing (1.0fte) Project description Current Natural Language Processing (NLP) systems, and especially large language models
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the training of these systems, is treated mainly as data rather than as a social practice shaped by people, culture, and context. This PhD project investigates how to make NLP systems emotionally and socially