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Field
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opportunities for collaboration with others and learning about a wide variety of topics in quantum computing and quantum information theory. What are you going to do? You are expected to: carry out original
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first line treatments for OSA, and works by delivering pressurized air to keep the airway open. Traditionally, titration of optimal PAP parameters was done in sleep labs, but home titration using auto
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explore how artificial intelligence can be used to predict the response to therapy in cases of acute rejection of the kidney graft. Using machine-learning techniques, you will assess kidney transplant
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with disabilities through inclusive Human-Computer Interaction (HCI) and participatory design methods. This PhD project will focus on methods and experiences in co-designing with stakeholders, especially
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prototypes with field tests, and (3) unravel the optimal mimic size for contrasting ecological settings in field experiments. Both PhD candidates will closely work together, and with a post-doc that will
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each other. This necessitates a multidisciplinary approach bringing together optimization, machine learning and behavioral modeling methodologies. In FlexMobility we propose a holistic approach to design
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machine learning solutions to optimize the component lifecycle directly contributing to a more circular economy. Information In the manufacturing landscape, determining whether a component should be
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in Computer Science, Artificial Intelligence, or related field. Solid programming and development skills (Python, Git, Bash). Experience with machine learning (e.g PyTorch/TensorFlow). Strong interest
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at TU Delft. In this project we also work together with experimental groups at TU Delft and beyond. The Delft Bioinformatics Lab has strong algorithmic and machine learning expertise, with a profound
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theory, discrete optimization and machine learning. In this PhD position you will focus on strain-aware genome assembly, variant calling and strain abundance quantification for viruses, bacteria and yeasts