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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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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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Uppsala University, Department of Information Technology Are you interested in developing new image analysis and machine learning methods for precision medicine and clinical decision support? Would
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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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, statistical methods, or machine learning is considered a merit. Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University´s rules and guidelines
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the student to progressively acquire knowledge in scientific methodology, experimental research, data analysis, and scientific communication. As part of your doctoral studies, your duties will include
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Documented ability to work in Python Experience with machine-learning methods for record linkage and text analysis Documented experience with machine-learning methods for image-to-text transcription
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nutrition, such as: analysis of time series data and dynamic processes, where signals and responses evolve over time. statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and
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for the learning and research tasks. Necessary qualifications: The applicant should by the date of admission to PhD studies have a second-cycle degree (e.g. MSc or equivalent) in environmental science or management
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for screening the subsurface to select areas with H2 -potential source rocks; - acquire and process new MT and controlled-source electromagnetic (CSEM) field data in targeted areas; - perform integrated 3D