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scans and use advanced data-driven methods, including artificial intelligence (AI) and machine learning to improve outcome prediction and patient stratification. deepen our understanding of the etiology
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holders, setting requirements on data quality and measurement conditions. Together with cardiologists, supervisors and colleague PhD students, you will further perform human testing of several prototype
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candidate you will: Collaborate closely with the experimental team that acquires these multiscale data Analyse rat MRI data, including integration with histology and calcium imaging Combine data across
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simulations. Job Description Are you passionate about bridging computational modeling with clinical cardiology to solve real-world healthcare challenges? We're seeking a PhD candidate to develop innovative
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shifts in cell state and cell fate. Integrate spatial transcriptomics data to anchor these predictions in tissue context. Develop machine learning methods (e.g. graph neural networks, variational
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with exceptional precision and in unexplored energy regimes. We use a crossed molecular beam machine with a Zeeman decelerator, which enables precise control over the velocities and quantum states of
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-antibodies. You will focus on the identification of these antibodies by using mass spectrometry based de novo sequencing, machine learning and AI-tools to interpret the data. Your job The primary objective
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provide a comprehensive package of study programmes and research. In our teaching, we use the Problem-Based Learning (PBL) method. Students work in small groups, looking for solutions to problems themselves
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Are you passionate about dynamical systems and system theory? Are you interested in making the design process of complex dynamical systems simpler by smart new tools for systems engineering? Are you
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through our research to issues from all around the world. Our six faculties combined provide a comprehensive package of study programmes and research. In our teaching, we use the Problem-Based Learning (PBL