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enhance real-time decision-making in road traffic management. The project aims to bridge the gap between recent advances in AI and machine learning, in particular, multimodal and instruction-tuned
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escape. To monitor these mutations and to understand their impact, it is crucial to analyse genomic big data efficiently and accurately. Genomes are studied through genome sequencing, but
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trajectories? Passionate about archival research and oral history? Self-motivated and ready to learn new research skills? The Department of History is looking for two PhD candidates to undertake archival and
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/jobs/354812/phd-student-self-learning-metam… Requirements Additional Information Website for additional job details https://www.academictransfer.com/354812/ Work Location(s) Number of offers
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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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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
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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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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