377 data-"https:"-"https:"-"https:"-"https:"-"UCL" Fellowship positions in United Kingdom
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in aeroacoustics, with a strong emphasis on data analysis and a deep understanding of aeroacoustics fundamentals. Demonstrate excellent communication skills, both written and verbal, as evidenced by
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successful at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in the Candidate Information document on our
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scale. The successful candidate will be responsible for: safely shredding cells using a bespoke instrumented, stabilised shredder; recording data for LCA including mass and energy balances, energy and
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provide information of what criteria will be assessed at each stage of the recruitment process. Further Information At King’s, we believe that the diversity of our community and a culture that is welcoming
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, to generate crucial information revealing the cellular roles, functions and underlying mechanisms by which MICL regulates immunity. The focus of this work will be to elucidate the components of MICL involved in
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, including fitness and health facilities, staff discounts, travel schemes and many more. To find out more about what we can offer you, follow the link to our benefits website Further information is available
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stakeholder partners, data collection and analysis, and disseminating findings to create impact. This is a key role in a major new programme of social science research, funded by a philanthropic organisation
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for generating data for associated research publications and other forms of dissemination. The majority of the analytic work will be stable-isotope tracer-based mass-spectrometry to assess changes in muscle
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portfolio. You will be required to have strong organisational and data analysis skills. You will be expected to plan and conduct work using approaches or methodologies and techniques appropriate to the type
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, advanced sensing techniques, sensor and operational data fusion, data analytics, and machine learning algorithms for condition monitoring, fault diagnosis, and early fault prediction in electric vessels