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relevant to setting a roadmap for ongoing experiments, as well as recently developed applications of tensor network techniques to large-scale partial differential equations. We are advertising two positions
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collaborative links thorough our collaborative network. The researcher should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely related field. You have an
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to understand and predict how technologies evolve — from artificial intelligence to net-zero innovations in energy, transport, and carbon capture. By building a global database on technological progress, we seek
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out rigorous and impactful research into the computational mechanisms of human learning using deep neural network models, and disseminating the findings within the research group, across the wider
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The post holder will develop computational models of learning processes in cortical networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity
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leader Pedro G. Ferreira and other members of the Beecroft Institute of Particle Astrophysics and Cosmology. The post holder will be a member of a disparate research network working independently to carry
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comfortable budget to conduct both project-related activities and activities related to their independent career development; iv) benefiting from the team wide academic and not-academic network, including
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and inclusive culture. Diversity is positively encouraged, through our EDI Committee, working groups and networks, for example eng.ox.ac.uk/women-in-engineering, as well as a number of family friendly
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Computational Neuroscience and related fields as part of the Medical Research Council, UKRI grant “Algebraic topology bridging the gap between single neurons and networks”. They will be expected to conduct
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of early tissue responses in vaccination with mRNA vaccines (MechRNA) as part of the larger the Lymph nodE single-cell Genomics AnCestrY and ageing (LEGACY) Network. This project involves profiling the intra