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to automate scientific discovery in both the natural and social sciences. The postholder will contribute to one or more of the following strands: • Foundational work on large-scale/foundation models and
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Institute of Particle Astrophysics and Cosmology (BIPAC), on research aimed at extracting cosmological information from large-scale structure (LSS) and Cosmic Microwave Background (CMB) probes on very large
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. About the Role The post is funded for 3 years and is based in the Big Data Institute, Old Road Campus. You will join an interdisciplinary team of researchers spanning imaging science, machine learning
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of therapeutic genomics, leveraging large-scale functional genomic datasets and cutting-edge computational resources, including university HPC clusters and AWS. The post-holder will advise colleagues on data
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly
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between the two linked studies as well as taking the lead in the large-scale qualitative secondary analysis of interview data from multiple sources. In this role you will be expected to contribute
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be close to the completion of a PhD/DPhil in epidemiology, biostatistics or big data, along with demonstrable experience of working with population registers and large datasets. With proven
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funding applications or permanent academic positions. About you The successful postholder will hold a PhD/DPhil in geophysics, Earth sciences, or a closely related field. The ideal candidate will have
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We invite applications for a Postdoctoral Researcher to join the research group of Professor Christopher Yau ( http://cwcyau.github.io ) at the Big Data Institute, University of Oxford. This post
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relevant for hadron collider synchrotrons at the high-energy frontier, such as the Large Hadron Collider (LHC) and its High Luminosity upgrade (HL-LHC) at CERN, the European Laboratory for Particle Physics