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Injection Systems (CIS) — natural protein machines used by bacteria to deliver molecular cargo. The group's mission is to understand the structure, function, and application of CIS for use in both
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Source (ESS), Sweden, the European Molecular Biology Laboratory (EMBL), Institut Laue-Langevin (ILL), France, the International Institute of Molecular Mechanisms and Machines, (IMOL), Poland, and the
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Source (ESS), Sweden, the European Molecular Biology Laboratory (EMBL), Institut Laue-Langevin (ILL), France, the International Institute of Molecular Mechanisms and Machines, (IMOL), Poland, and the
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HCI and cybersecurity, to cancer research tools and methods for numerical analysis and machine learning. The research work takes place in a multidisciplinary team with a focus on image processing with
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Institute of Molecular Mechanisms and Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. Your work may include clinical and biomedical projects. It may
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integration of AI-based vision and active machine learning to optimize the efficiency of the process. Writing publications and present research results from the project on conferences. Collaboration with
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description and working tasks The project will develop privacy-aware machine learning (ML) models. We focus on data-driven models for complex and temporal data, including those built from synthetic sources
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transitions and universality for spectral statistics of random matrices and their applications in high-dimensional statistics, machine learning and probability theory. The Department of Mathematics at KTH
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statistics, unsupervised machine learning, optimisation, model predictive control. Experience in financial mathematics. Having high integrity, be process-oriented and able to work independently. Being able
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. Teaching may also be included, but up to no more than 20% of working hours. The position includes the opportunity for three weeks of training in higher education teaching and learning. The purpose