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and electroencephalography (EEG), combined with advanced machine-learning methods, such as multivariate patterns analysis (MVPA). This approach will explore how neural representations evolve with eye
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control strategies for object manipulation in case of frictional contacts, capable of learning from and adjusting to environmental uncertainties, utilizing nonlinear control and machine learning techniques
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for analysis, design and verification do not scale well with increasing complexity. Furthermore, new powerful algorithms for machine learning are increasingly being used for control engineering purposes, further
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teaching expertise and have been awarded a PhD or have the corresponding research competence or some other professional expertise that is of value in view of the subject matter of the post and the duties
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the protection of data and computer resources to the greatest extent possible. Particularly important for the coming years is knowledge of technologies such as machine learning and virtualization and how they can
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experience. Subject Distributed Systems Subject description Distributed Systems focuses on how to program software systems on top of different kinds of computer networks, including mobile and dynamically
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science, statistics, engineering, or a similar field. Practical experience in big data or machine learning methods. The candidate must know how to program in Python and R. The candidate must be driven and can work
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on power electronics, electrical machines, and power grids at Lund University. IEA has 2 professors, 6 associate professors, 1 postdoc and 18 PhD students and a laboratory technician. The activities
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/machine and organization) and is often carried out in development projects with strong elements of user participation and production of prototypes in different levels of detail. By integrating
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libraries (scFv and Fab), we are currently developing an antibody library based on a so-called single domain concept and we expect to develop other display platforms and machine learning/AI competencies