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funded by UKRI EPSRC and is fixed term for 12 months. You will be contributing to joint UKRI EPSRC – NSF CBET project on sustainable computer networks, with a focus on carbon emissions reduction and
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to 31st May 2028). The RADlab at University of Oxford is seeking to recruit a Postdoctoral Researcher for the Neural-driven, Active, and Reconfigurable Mechanical Metamaterials (NARMM) project. Candidates
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with other researchers in designing behavioural tasks and neuroimaging/neurostimulation experiments for investigating the neural mechanisms underlying emotional approach/avoid choices. You will use fMRI
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mechanisms identified in rodents will therefore be used to inform our understanding of human cognition and behaviour. Your duties will include acquiring rich neural data sets in awake behaving animals, and in
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applications Help ensure the smooth running of the network and key IT systems Support compliance with data protection and security policies You will also work closely with colleagues to understand user needs and
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programming skills and expertise with computational methods for neural/behavioural data analysis. You will have experience in conducting task-based functional neuroimaging and/or behavioural experiments, and
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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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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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depending on funding. The Oxford Ion Trap Quantum Computing group currently hosts one of the world’s highest performance networked quantum computing demonstrators, capable of remote Bell-pair production
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crystalline resins for use in two-photon polymerization. New forms of imaging hardware will be utilized in collaboration with partners to provide greater understanding of the polymer network morphology and how