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We are looking for a Postdoctoral Researcher in Diffusion MRI Methods, the post will be based within the Oxford Centre for Functional MRI of the Brain (FMRIB), reporting to Professor Karla Miller
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and in-vivo germ-free methods. In addition to research, the post holder will provide guidance to less experienced members of the research group. The post-holder should hold, or be close to completion
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optimality with computational efficiency. Reinforcement Learning through Stochastic Control. We will develop methods from stochastic control, which will provide a mathematically grounded approach that has a
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geothermal processes along the volcanic arc, inform future field deployments, and serve as benchmarks for the development of new deep learning methods for volcanic seismicity. This project will apply deep
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central role in developing and validating these advanced human model systems, applying molecular, imaging and electrophysiological methods to characterise disease-relevant phenotypes and drug responses
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cell sampling and biobanking methods for endangered species. This work will support global conservation efforts at a time when over one million species face extinction. The post holder will be involved
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of the resulting materials will be undertaken using thermal, mechanical and rheological methods, as well as using spectroscopy and GPC methods. Materials will be tested in applications and end-life recycling
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(or be near completion), with established expertise in Computational Mechanics, Constitutive Modelling, and the Finite Element Method. Informal enquiries may be addressed to Prof. Laurence Brassart
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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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methods (Uphoff PNAS 2013; Robb, Sci Reports 2019; Zagajewski, Nature Comm Biol 2023, Chatzimichail, Lab-on-a-chip 2024) and applying them to proteins functioning on DNA and RNA (Stracy, PNAS 2015; Mazumder