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modelling experience, an ability to work in a multidisciplinary team and engage confidently with partners. You will have a track record of publishing high impact journal articles, and will have a commitment
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can support both health and mobility outcomes. The successful candidate would be responsible for the more technical parts of this project, leading the computational modelling of charging infrastructure
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We are looking for a motivated and talented postdoctoral-level researcher with experience in executable modelling to join a cutting-edge project developing Digital Twins for rare diseases. This is a
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alongside computational biology approaches to map epigenetic changes driven by WNT/GSK3 signalling in ESCs. This collaborative project offers access to world-class expertise, state-of-the-art resources, and
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this project, leading the computational modelling of charging infrastructure required to meet electric mobility goals. You would work closely with another researcher on the project focussing on associated
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or equivalent experience in an appropriate discipline A background in numerical ice-sheet, glacier or fracture modelling, or equivalent experience Robust experience with computer coding (e.g., Python, C++) Track
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of fungal pathogens. The successful candidate will make extensive use of a range of in vivo models of fungal infection and will have access to the wide range of transgenic tools and in vivo immunology
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on high performance computing systems in a way that is suitable for operational use. Implement and test different ML architectures, such as convolutional and encoders-decoder ANNs for predicting flooding in
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, supported by PEACEPLUS, a programme managed by the Special EU Programmes Body (SEUPB). The PEACEPLUS programme is co-funded by the European Union, the Government of the United
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of fungal pathogens. The successful candidate will make extensive use of a range of in vivo models of fungal infection and will have access to the wide range of transgenic tools and in vivo immunology