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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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selection criteria Knowledge of sensors and measurement techniques Experience from the industry providing sails for merchant ships Experience with Computational Fluid Mechanics Knowledge of machine learning
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appointment. Job duties Mentoring new PhD students in numerical computational projects. Conducting comprehensive literature reviews in machine learning for subsurface flow and well performance and supporting
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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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machine learning. The project combines methodological research in statistics with applications to large-scale social science data. The successful candidates will have the opportunity to collaborate closely
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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on clinical complications, and use machine learning to develop and validate predictive models to identify high-risk patients. The research aims to individualise inpatient care, reduce hospital-acquired
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, physiology and disease development; profile root and leaf microbiomes using amplicon sequencing; analyse integrated microbiome and phenotyping datasets; contribute to machine-learning models predicting
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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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meet the requirements for admission to the faculty's doctoral programme in Engineering Cybernetics . Strong programming skills, in particular Python, and practical experience with modern machine learning