46 wireless-sensor-networks-postdoc Postdoctoral positions at University of Oxford in Uk
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We are looking to hire postdoc with a background in MRI physics/engineering, between whom we will gain experience in: Biophysical modelling Bloch-based physics simulation Multi-modal quantitative
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of the research group, including postdocs, research assistants, technicians, PhD and project students, as well as to represent the PI and ISML when required. You will hold a Masters or PhD degree (or be close to
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and Shock Mechanics Laboratory. You will be asked to provide guidance to less experienced members of the research group, including postdocs, research assistants, technicians, PhD and project students
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settings. We are seeking a highly motivated postdoc to conduct research into this fast-moving area. Directions may include investigating quality evaluation methods for multi-agent systems, attack surfaces
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(notably MCP, A2A). Note that the successful candidate will work in collaboration with two other postdocs on a closely aligned project “Rethinking multi-agent systems in the era of LLMs”, funded by
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for applications is 12:00 on Monday 7th July 2025. Interviews will be held as soon as possible thereafter. At the Dunn School we are committed to supporting the professional and career development of our postdocs
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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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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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we are committed to supporting the professional and career development of our postdocs and research staff. To help them thrive and achieve their ambitions, we have created a comprehensive range of
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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