149 parallel-and-distributed-computing-phd-"Meta"-"Meta" positions at King's College London
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& Health Informatics. Contact details:Professor Richard Emsley. Richard.emsley@kcl.ac.uk Location: Denmark Hill Campus. Category: Academic & Teaching. About us: We have an exciting opportunity for an early
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develop and lead a research programme sustained through external peer-review funding. The Reader’s interests and activities should align with and shape at least one of the three key BH&CH themes: Careforce
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provide a generous salary plus running expenses of up to £30,000 for 18-24 months. They will enable appointees to establish their own research programme at King’s, focussed on establishing a competitive
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for more information. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria 1. PhD degree in Engineering, Computer
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successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria 1. Hold a PhD or about to obtain a PhD degree in Computer Science, Software Engineer
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Research Project titled “Harnessing electron-phonon interactions in nanoplasmonic solar energy conversion”. The goal is to develop new computational methods that will enable design of metallic nanoparticles
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: Essential criteria PhD qualified in relevant subject area (Immunology, Biophysics, Biochemistry, etc) * Expertise in biomechanics, both the theory and methods Expertise in T cell biology, immunology, cancer
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campuses, our academic programme of teaching, research and clinical practice is embedded across five Departments. About the role We are looking to recruit a Postdoctoral Research Associate with a PhD in
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scientists. Based across King’s Denmark Hill, Guy’s, St Thomas’ and Waterloo campuses, our academic programme of teaching, research and clinical practice is embedded across five Departments. About The Role
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision