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learning. The post-holder will be familiar with the use of these techniques and experience of dataset construction and data mining will be essential. The successful applicant will have completed an MPhil/PhD
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no.: 4331 Among the many reasons to research and teach at the University of Vienna there is one in particular, which has convinced around 7,500 academic staff members so far. They see themselves as
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under real-world conditions. The role includes collaboration with leading 2D materials manufacturers, offering potential for interdisciplinary research and travel. About You You should have a PhD (or be
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sufficiently versatile to rapidly acquire the required capacity. You will have : A PhD in gut microbiology or closely related field Good knowledge of gut modelling and general microbiology Experience in
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to be expert at all aspects – but instead hopefully versatile and willing to learn and expand their experience. Open to all: We run a diverse research group, supporting varied gender, ethnicity and
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design, delivery, and evaluation of a multi-school research study investigating the impact of mathematical storytelling on secondary students’ mathematics learning and related outcomes. Working closely
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major NERC funded projects to make the first detailed measurements of turbidity currents in action in the deep-sea, and to develop novel technologies for monitoring these seabed sediment flows. Turbidity
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are comfortable navigating complex HPC environments and wrangling large datasets. You have experience with modelling through state-of-the-art machine and deep-learning methods and with hands
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scientific publications, patents, and seeing collaborators translate our work into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and
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), to develop systems that improve the efficacy of machine learning-based technologies for healthcare applications. You must hold a PhD (or be near completion) in a field such as AI, computer science, signal