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on research pertinent to the project. By scaling up data, compute and model size, large language models (LLMs) have gained an impressive and ever growing array of capabilities. The next phase of development
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of applying them to data. Collaborative endeavours with members of the IPMU and Oxford groups is highly encouraged. You will have the opportunity to teach. Applicants should have a PhD (or close to completion
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research income generation. You will also have experience in working with large micro databases and grouped data. Experience of independently managing a discrete area of a research project, working in
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genome encodes gene expression levels. You will undertake large scale data generation from primary human samples using a method recently pioneered by the host laboratory (Hua et al., Nature 2021 https
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investigating how dopaminergic and serotonergic systems interact in the primate frontal cortex to support learning and decision making. About the department The Department of Experimental Psychology is a large
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of extension by 1 year. This project involves searching new particles using the data from the ATLAS experiment at the Large Hadron Collider. The successful candidates will analyse data from the ATLAS experiment
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manufacturing. AI methods will then be applied to this large database to inform optimal processing parameters that will produce components with reliable material properties. The process will be validated in a
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for monitoring large carnivores. This is a fixed-term position for one year, with the possibility of annual extensions up to a maximum of three years, subject to continued funding. About you The successful
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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