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cell (and one cell–cell interaction) at a time. You will work with large-scale single-cell and spatial transcriptomics data to develop and apply single-cell foundation models — generative machine
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supervised by experts in combinatorial optimization, machine learning and fairness-awareness in algorithmic decision support, and the Eurotransplant headquarters in Leiden, where access to the domain expertise
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deterioration can be avoided. This PhD is part of the EU Horizon QleanUP project, through which you will directly engage with stakeholders and do your research as part of a large international consortium. Within
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this PhD project, you will: investigate cardiovascular function and risk factors in critically ill patients using electrocardiograms (ECGs) and computed tomography (CT) data from a very large (> 20,000 ICU
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, or related field; Solid background in machine learning, deep learning and foundation models such as Large Language Models; Strong programming skills (Python/C++); Proven interest in generative models
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, or related field; Solid background in machine learning, deep learning and foundation models such as Large Language Models; Strong programming skills (Python/C++); Proven interest in generative models
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predictive optimization, behavioral modeling and machine learning. There is vivid interaction within the group to foster collaboration both with scientific and social activities. The PhD candidate will also
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work in our multi-disciplinary team, including AI-experts, MRI-physics experts, and clinical experts. You will conduct new academic research combining machine learning and medical physics. Your research
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join us as a PhD candidate. You will work in a highly interdisciplinary group, at the intersection of physics, machine learning and theoretical neuroscience. Our group is focused on investigating
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cell (and one cell–cell interaction) at a time. You will work with large-scale single-cell and spatial transcriptomics data to develop and apply single-cell foundation models — generative machine