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Field
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of approaching reconstruction and variability analysis. The project combines applied mathematics, computational imaging, and structural biology. You will develop algorithms, implement and test software tools, and
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to improve our understanding of disease and the effectiveness of treatments, and implementing AI algorithms to deliver safer and more efficient care. The student will have access to a unique training programme
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event-based cameras. 2. Developing the first-ever AI/ML algorithm to predict the transition in real time. This will be implemented in benchmark transient multiphase flows, such as bubbly flows, turbulent
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precision medicine based on gene sequencing time series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related
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algorithms for resource-efficient hydroponics and evidence-based frameworks for integrating green space exposure for improved student wellbeing. This project will potentially enhance urban food resilience
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the Unconventional Communications and Computing Laboratory (UC2), led by Dr Michael T. Barros, which develops modelling and algorithmic methods for networked communication and computation under real-world constraints
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on real-life data from the maritime industry. As part of the PhD, you will be following advanced courses to extend your skills, implement and test algorithms, and learn to write scientific papers. As part
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Technology, Dep. ETI / Embedded Systems, we are looking for a researcher as of the 01.04.2026. Your tasks: Development of architectures and algorithms for adaptation of time-triggered systems based
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conducted to assess the feasibility of prototypes in terms of activity tracking, updating game elements, and visualisation capabilities. The second objective of the thesis is to develop models and algorithms
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algorithms for resource-efficient learning, for example via data selection and filtering (leveraging that not all data is equally informative). You will also investigate complementary approaches that reduce