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Field
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advanced statistical machine learning, reinforcement learning, and gen-AI-driven decision models for supply chain and operations optimization. • Design scalable algorithms for demand forecasting, risk
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slicing. - Develop advanced AI/ML algorithms and data analytics techniques to automate and optimise exposure requests, adapted to available resources and real-time demand. - Propose and
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integration of signal processing and machine learning methodologies aiming to interpret distributed acoustic sensing (DAS) data from production wells (both new and previously acquired sensor data). The main use
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on terrestrial ecosystems in its new range. This project will investigate dispersal and distribution of pink salmon carrion and its effect on vegetation communities in coastal tundra ecosystems in northern Norway
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of diagnostic and prognostic algorithms. Electronic Prognostics Systems: Facilities equipped to assess the health and predict the remaining useful life of electronic components, supporting studies in electronic
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thus including sensing systems, tool condition features selection, algorithms for automated signal preprocessing, feature extraction and decision making based on ML and AI. An integral part of
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that shape the design of these circuits. The lab is dedicated to medical algorithmics on the applied research front, emphasising technologies implementable within hospitals. Notably, the lab’s medical image
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to analyse cardiovascular images, primarily focusing on MRI. In your research you will train models to learn a distribution of normal cardiac anatomy and function (including motion) from healthy subjects. By
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(HPC) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution
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persists, even for the most powerful sensors operating in this way. A drastic departure from this sensing architecture is “multistatic” radar – enacted by a coherent network of spatially distributed sensors