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erythrocytes, alongside biomarkers of inflammation and oxidative stress. Using combined laboratory and clinical data, empirically derived algorithms for subphenotype identification will be developed through
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learning, Efficient Algorithms and High Performance Computing), and Physics (Image Formation Modelling). Your project is part of the DUAL-IMPACT project, which focuses on the development of new data-driven
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: Transparency. As part of this doctoral project, you will develop novel knowledge representation techniques, algorithms for human-in-the-loop optimization, and interactive tools that combine graphical and natural
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-static beamforming methods, and semi-tomographic reconstruction algorithms that enable high-quality 3D visualization of the abdominal aorta. In addition, you will develop algorithms for segmentation
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of service. The project is conducted in collaboration with two clusters at the Department of Mathematics and Computer Science of TU/e: Data and Artificial intelligence . Novel learning algorithms will
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donor management, donor health protection, health data use, and algorithm-supported decision making. 2. Stakeholder Perspectives Using focus groups and semi-structured interviews, you will explore
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), Computer Science (Machine learning, Efficient Algorithms and High Performance Computing), and Physics (Image Formation Modelling). Your project is part of the DUAL-IMPACT project, which focuses on the development
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. Guidance on writing, presentation, and career development. Flexible working hours. A shared interest in producing high-quality research results. Where to apply Website https://www.academictransfer.com/en
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different incentives, mechanisms and regulatory scenarios, evaluating their performance with respect to different objectives and their trade-offs. Developing decentralized and bi-level algorithms to help
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user studies, develop novel algorithms, build immersive/augmented realities, and validate your solutions in real-world settings. This PhD is ideal for candidates interested in one or more of the