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, micro-CT, particle size analysis, calorimetry, and synchrotron experimental measurement techniques. Knowledge of AI-based and machine-learning methods is also beneficial. For further information about a
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doctoral degree Collect, structure and assess relevant sensor, operational, maintenance, incident and cost data Develop and validate statistical, causal and/or machine-learning methods and turn the results
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thinker, eager to learn new experimental techniques, and enjoy collaborating with researchers from different disciplines as well as industrial partners. Furthermore, you meet the following requirements: 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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to the development of sustainable materials for the hydrogen economy. You are an independent thinker, eager to learn new experimental techniques, and enjoy collaborating with researchers from different disciplines as
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, Mathematics, Engineering or a related discipline, with an interest in AI applied to complex and safety-critical systems. Good knowledge of Machine Learning and Deep Learning methods, including experience with
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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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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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systems, or continuous-time and discrete-time LTI systems theory is a plus. Experience with mathematical modeling, optimization, numerical computation, algorithm development, or machine learning. Prior
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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