667 postdoc-in-thermal-network-of-the-physical-building Fellowship research jobs in United Kingdom
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jobs website . Online applications will be accepted by the automated system until 10pm of the closing date. Any queries regarding the application process may be addressed to jobs@lshtm.ac.uk . Please
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; Chemistry; Computer Science; Ecology; Engineering; Environmental Sciences; Mathematics/Mathematical Sciences; Medicine; Natural Sciences; Physics; Psychology; Veterinary Sciences. This Fellowship is intended
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the refocusing of research. Geosolutions Leeds brings together world-leading expertise in geology, engineering and social science to deliver an integrated systems approach to energy geoscience that will meet Net
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-depth characterisation and annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based
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interest in the role of rhythmic processes in cognition. The post is available for 12 months in the first instance with the possibility of further extension. About the role The postdoc researcher will work
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techniques to enable large-scale data search across Personal Online Datastores (pods) hosted on distributed pod servers, addressing both keyword-based search and SPARQL querying. EPRESSO will build on and
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schemes and development opportunities. We support staff wellbeing with flexible working options, work-life balance initiatives and support for physical and mental health. You can find more detail on all
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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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annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where
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at national and international conferences. The project is based around constructing physics-informed neural networks (PINNs) to model the fluid dynamics of Earth’s core where the global magnetic field is