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Field
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at the intersection of computer vision, micro-electronics analysis, and hardware security, and will work under the supervision of researchers within the Department of Intelligent Systems. The PhD researcher will be
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machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in industrial furnaces
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with European industry. The EISLAB division at Luleå University of Technology conducts research in electronic systems design, sensor systems, cyber-physical systems, the Internet of Things and machine learning
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or environmental engineering, Mathematics (Operations research) or Computer Science or Machine Learning). Documented knowledge of relevant methodologies, both quantitative and/or qualitative, at master’s level
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Machine Learning within the School of Medicine at the University of Limerick. This is a methodologically focused PhD for candidates with strong quantitative backgrounds who wish to develop novel statistical
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low latency and high capacity optical switched AI computer network architecture empowered by the developed photonic integrated WDM switches and controls. The PhD candidates will contribute to the TU/e
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learning and computer systems. The successful candidate will join an international and collaborative research environment and contribute to advancing efficient AI systems. Are you motivated to take a step
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and vegetation development. This PhD project is part of a larger interdisciplinary research initiative aiming to enable a transition towards more data-driven and environmentally responsible maintenance
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. The EISLAB division at Luleå University of Technology conducts research in electronic systems design, sensor systems, cyber-physical systems, the Internet of Things and machine learning, and works on
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willingness to acquire advanced longitudinal and machine-learning methods. Programming skills in R (or a demonstrated ability to acquire them quickly). An interest in working with large, real-world data from