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data assets, and in the context of the world’s largest longitudinal population studies, many hosted here at the Big Data Institute, as well as other international initiatives. To be considered, you must
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to reconstruct subsurface defects; Implement image/signal‑processing or machine‑learning pipelines for automated flaw characterisation; Collaborate with the Federal University of Rio de Janeiro, including short
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Computer Science or a related topic. Applicants at the PDRA level must have a PhD in NLP or machine learning. Substantial knowledge of Natural Language Processing (NLP) and machine learning methods is essential, as
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, working with some of the world’s largest single-cell data assets, and in the context of the world’s largest longitudinal population studies, many hosted here at the Big Data Institute, as well as other
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further including to automated platforms to generate large statistical data sets. We will also experiment with untried higher spatial resolution techniques. The large, multi-dimensional data sets will be
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for candidates to have the following skills and experience: Essential criteria PhD qualified in mathematical, physical or computational sciences Experience in using machine learning methods to analyse datasets
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computing, computer architecture, programming models and high performance computing. These are your qualifications: Must-haves: Completed doctoral/PhD studies in Computer Science or a closely related field
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About the Role We are seeking an enthusiastic and motivated postdoctoral researcher to apply advanced data analytics and machine learning techniques to real-world clinical data in the field of viral
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of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine learning “emulators” of multiple ice sheet and glacier models, based on large ensembles
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in machine learning and/or computer security and Experience working with LLMs or agent-based systems. Informal enquiries may be addressed to adel.bibi@eng.ox.ac.uk For more information about working at