35 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Aarhus University in Denmark
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patterns, and extreme climate events remains a subject of debate. Using a combination of climate modelling, statistical methods, and machine learning, ArcticPush aims to uncover the conditions under which
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Natural Language Processing, Machine Learning, or a similar area. Expertise in large language model architectures and training paradigms (transformer models, fine-tuning strategies, RLHF, etc.). Interest in
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and PhD students working on various aspects of computational biology and hosts a number of collaborations with the Hospital. BiRC hosts the genomeDK supercomputer, which will be available
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Anatolia and from the Tigris to the Mediterranean with a focus on visual culture. Qualifications Applicants must hold a PhD degree in Classical Archaeology or closely related disciplines and be able
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programme. Academic staff contribute to the teaching. English is the preferred language in the laboratory, at meetings and at seminars. The department employs approx. 500 people from all over the world, and
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scientific areas. We educate both Bachelors and Masters of Science in Engineering and around 825 students are enrolled in our study programs. Furthermore, we also offer an ambitious PhD program. Our PhD
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are enrolled in our study programs. Furthermore, we also offer an ambitious PhD program. Our PhD students have high academic ambitions and deliver high-quality results for both the private and the public sectors
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research and teaching environment and activities. We expect you to teach and supervise students at Bachelor’s and Master’s level and to carry out research of the highest international standards, which
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directed to Associate Professor Helle Strandgaard Jensen (hs.jensen@cas.au.dk ) Qualifications A PhD in history, cultural studies, anthropology, sociology, media studies or related areas focusing on modern
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approaches—combining additive (MIG welding-based) and subtractive (CNC machining) processes—for the refurbishment of industrial components. The postdoc will focus on characterizing material interfaces and