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About the Role You will develop and apply novel computational methods to quantify the societal impact of fundamental science discoveries. Candidates close to completion of their PhD will initially
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-term persistent infections, as well as on newly emerging variants of concern (VOCs). We are seeking a highly motivated candidate that has obtained (or will obtain soon) a PhD in a relevant subject (i.e
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across the clade, and reconstruct geographic distributions of key nodes and fossil taxa. About you You will hold or be close to completion of a relevant PhD/DPhil, together with relevant experience. You
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2019 https://doi.org/10.1038/s41596-018-0110-x and Lara et al ., arXiv:2503.21396 https://doi.org/10.48550/arXiv.2503.21396 )). In parallel with your experimental work, you would develop theoretical
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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scholars in Law and two PhD students (one in Law and one in Computer Science/Data Analytics), as well as with international, European and national stakeholders involved in the CURE project. The post-holder
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computational workflows on a high-performance cluster. You will test hypotheses using data from multiple sources, refining your approach as needed. The role also involves close collaboration with colleagues
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Mobility Reading Group led by Nobuko Yoshida. The successful candidate will be located in the Department of Computer Science Reporting to Professor Nobuko Yoshida, the post holder will be responsible
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research programme at Oxford. Candidates should hold a PhD in biomedical engineering, computer science, medical physics, statistics, or a related field. A strong track record of first-/senior or co-author
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research programme at Oxford. Candidates should hold a PhD in biomedical engineering, computer science, medical physics, statistics, or a related field. A strong track record of first-/senior or co-author