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Field
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About the Role You will develop and apply novel computational methods to quantify the societal impact of fundamental science discoveries. Candidates close to completion of their PhD will initially
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to the clinic The post holder will be based in the Department of Biomedical Computing as part of the School of Biomedical Engineering & Imaging Sciences, King’s College London, a vibrant community of engineers
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(or have recently submitted) in a relevant subject (climate, meteorology, physical geography, earth and environmental sciences, physics and astronomy, applied mathematics, statistics, computer science
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have completed, or be close to completing, a PhD/DPhil in a relevant quantitative field such as computational social science, computer science, or cognitive science. They will have a demonstrable track
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Machine Learning, Statistics, Computer Science or closely related discipline. They will demonstrate an ability to publish, including the ability to produce high-quality academic writing. They will have the
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involved in research projects and scientific surveys. You prepare and complete a habilitation thesis. You publish nationally and internationally and give lectures. You are involved in the coordination
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the performance of lithium ion technologies. To support the programme, the post holder will be required to carry out research on characterisation of battery degradation, with a particular focus on the application
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highlights the urgent need for novel approaches. Antimicrobial peptides (AMPs) are an emergent technology platform which are cost-effective to manufacture and have potential to control wound infection. Despite
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are seeking to appoint a postdoctoral research associate as part of a UKRI Future Leader Fellowship funded research programme. The successful candidate will work as part of a team to develop and apply deep
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are seeking to appoint a postdoctoral research associate as part of a UKRI Future Leader Fellowship funded research programme. The successful candidate will work as part of a team to develop and apply deep