672 postdoc-in-thermal-network-of-the-physical-building Fellowship positions in United Kingdom
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in any field of Modern Greek Studies, including religious minorities and interdisciplinary approaches, who can make an original contribution to our research culture in this area. Preference may be
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to provide support on the application and interview process. Discover our benefits, visit Your Benefits website. We welcome applications from UK, Europe and worldwide and aim to make your move to the UK as
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candidates with expertise in any field of Modern Greek Studies, including religious minorities and interdisciplinary approaches, who can make an original contribution to our research culture in this area
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development. This entitlement, from the Concordat to Support the Career Development of Researchers , applies to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP
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and timely manner Attend taskforce meetings and liaise with UKRI and external stakeholders Work to proactively build a network of others working on issues of data access in the UK and internationally
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hydrometeorological and climatological) hazards, involving the quantification of effects on individual assets/infrastructure components (e.g., buildings) as well as network-level and distributed-system disruptions; 2
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mosquito vector. This is to dissect the protein network and how key novel signalling proteins are involved parasite proliferation stages. The work will involves gene targeting both conditional knockdown and
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flexible working options, work-life balance initiatives and support for physical and mental health. You can find more detail on all of this and more at https://www.qub.ac.uk/directorates/HumanResources/pay
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partnerships are creating leaders in technology and management globally. Learn more about Cranfield and our unique impact here . The Centre for Propulsion and Thermal Power Engineering is around 80 staff strong
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-life environments. The Role: As Research Fellow on the COG-MHEAR project, you will have the opportunity to use your strong background in deep neural networks and multimodal hearing-aid signal processing