24 wireless-sensor-network Postdoctoral positions at University of Oxford in United Kingdom
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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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of Oxford. The post is funded by the National Institute for Health and Care Research (NIHR) and is fixed term for 24 months. The researcher will develop multi-sensor 3D reconstruction algorithms to fuse
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participating in the training and management of PhD students. Solid-state spin photon interfaces are central to emerging quantum technologies, such as optical quantum networks and quantum sensors. Point defects
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. This can involve IoT connected devices, physical sensors or other instruments, including non-intrusive methods and inferences from a variety of data sources. You should have some experience with experimental
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system with integrated sensors. You should hold or be near completion of a PhD/DPhil with relevant experience in the field of robotics, biomedical engineering, information engineering, electrical
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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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specialist knowledge and experience in data acquisition, signal processing, and data analysis from wearable or non-wearable sensors and devices. You must be able and willing to travel away from Oxford, often
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participating in the training and management of PhD students. Solid-state spin- photon interfaces are central to emerging quantum technologies, such as optical quantum networks and quantum sensors. For example
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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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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