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. The project focuses on developing an integrated approach that combines machine learning techniques with physics-based models to estimate the health of various system components. The aim is that fault diagnosis
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image analysis and sensor technologies (e.g. RGB/NIR) for textile production, as well as using machine learning for process optimisation and performance prediction from fibre to finished product
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with the easy assignments and then, as you learn and become more experienced, progress to increasingly difficult/qualified work. Qualifications The requirements for the position are: At least a Master’s
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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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Learning and Control Laboratory , an interdisciplinary research group doing basic and applied research at the intersection of cybersecurity, control theory, and machine learning. Our vision is to develop
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states and the transcription factor combinations that drive them as well as predict new combinations with machine learning approaches. This project will encompass: analyse single-cell and multi-omics
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is also required. documented ability to teach in Swedish or English. In addition to academic qualifications, teaching and training experience from other contexts may also be considered, such as
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will also use focussed ion beam milling scanning electron microscopy (FIB-SEM) to prepare infected cells for in situ cryo-ET. The resulting tomographic data will be analysed by machine-learning assisted
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, machine learning, etc. Building a quantum computer requires a multi-disciplinary effort involving experimental and theoretical physicists, electrical and microwave engineers, computer scientists, software
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%). You will work at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model