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address this, you will adopt a novel "top-down" strategy, directly opposed to the current materials discovery methods, to accelerate materials development for creep-fatigue environments. Specifically, you
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. Application procedure This post is suitable for psychologists or data managers with a strong background in quantitative research methods and statistics and is available now. For additional information/informal
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experience in airway biology and advanced primary cellular models, integrating molecular, imaging and cell biology methods. Knowledge of CRISPR/Cas9 methods is welcomed. You must be a good team worker
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and the development of innovative design concepts, maximizing material properties and sustainable manufacturing methods. Qualifications: Strong background in aircraft design. Proficiency in Python
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methods is also desired. In our study we are investigating whether it is possible to predict how many nurses are needed on hospital wards from routinely collected data. You will have an interest in
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skills within the relevant clinical departments of University Hospital Southampton cancer services. The post is not formally recognised for training but there are well-developed site specialised
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, you will be based in the Aerodynamics and Flight Mechanics research group comprised of experts in theoretical, computational and experimental methods and our aim is to provide an environment in which
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be successful in the role you will have, or will be close to completing, a PhD (or equivalent professional qualifications) with strong qualitative research methods skills in a relevant discipline (e.g
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leaders, local authorities, and non-governmental organisations Required skills Demonstrable expertise in qualitative research methods, including experience with NVivo or other thematic analysis approaches
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synthetically challenging. You will develop methods to improve the synthesis of endohedral fullerenes, and look at further modification, particularly through the use of e-beam irradiation (e.g. ACS Nano 2020, 14