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an interdisciplinary team working across physical and computer science to develop new pathways to the design and discovery of inorganic materials as part of the Leverhulme Centre for Functional Materials Design. This
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, meaning that familiarity with one or more cloud-based platforms such as Google Earth Engine, Microsoft Planetary Computer and/or Amazon Web Server/similar is essential. It will also involve the development
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. The position gives excellent opportunities in publishing in high-quality forums. We expect the applicants to have a PhD degree (or close to completing one) in computer science, mathematics or statistics, with
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annual leave, plus 9 buildings closed days for all full time staff. Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm to see the value of benefits provided by
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techniques applicable. You should also have: A PhD degree (Research Associate) or a Master’s (Research Assistant) in computer science or a related area.* Familiarity with ICS and/or CPS. Excellent
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on computational modelling of the electrode/protein bioiterface. We are seeking highly motivated postdoctoral candidates willing to fully commit to an exciting, cutting-edge project. The skills we are looking
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computational modelling techniques, including recurrent and generative models. We are also in the process of developing different toolboxes to make these techniques more available across both our group and
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, in natural science and/or social science domains. Candidates should possess a PhD (or be near completion) in PhD in Computer Science, AI, Security, or a related field. You will have a Strong background
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Developmen t 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 PhD awarded in Computational
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. The successful candidate will work within a multidisciplinary team to unravel the metabolic drivers of HCC biology and transplant rejection through cutting-edge spatial multi-omics and computational metabolic