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of Computer Science, Norwegian University of Science and Technology (NTNU). The position offers the opportunity to work on cutting-edge research at the intersection of deep learning and computer systems. The successful
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will then develop XR applications that provide real-time guidance through visual, auditory, or haptic feedback in everyday situations. Using wearable devices, machine learning, and cognitive models you
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improved using machine learning techniques. The developed techniques will be applied to metrology of semiconductor samples. Job requirements You are an enthusiastic candidates with a ‘drive’ for applied
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will then develop XR applications that provide real-time guidance through visual, auditory, or haptic feedback in everyday situations. Using wearable devices, machine learning, and cognitive models you
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and hardware security assurance for embedded systems by combining advanced side-channel analysis, fault-injection techniques, AI- and machine-learning-assisted analysis, robustness evaluation, and
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benchmark chemometric and physics-informed machine learning models to monitor, forecast, and ultimately control critical process parameters, implanting these models in advanced control frameworks to optimize
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University of Science and Technology (NTNU) has a vacant position as PhD candidate in the field of machine learning for materials science. Your immediate leader will be the Head of Department. About the
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engineering disciplines, including structural mechanics, hydrodynamics and machine learning Strong programming skills in Python and/or MATLAB Experience with scientific computing, CFD/FEM software, potential
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Machine Learning, Reinforcement Learning, AI-based time-series forecasting English language skills, both written and spoken, corresponding to the scale C1 in the Common European Framework of Reference
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This PhD project, part of the REACT MSCA Doctoral Network, aims to develop an energy-efficient compute-in-memory (CIM) architecture using gain-cell memory for real-time edge learning, addressing