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, and access to leading high-performance computing facilities. • The valuable opportunity to join a cohort of innovative scholars collectively shaping the future of AI, through the cross
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low-coverage whole genome data Experience performing species delimitation models and understanding multi-species hybridization Proven ability to work with large datasets Experience working on a high
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and impact related to two EPSRC funded projects: ResTOrES (Resilience Toolkit for Offshore Energy Systems) and RENEW (Climate Resilient Heat Electrification for Net-Zero Emission Whole Energy). The
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of Quantum Computing (EPIQC) with Prof. Chong Li . Specifically, the job requires expert knowledge and hands on experience in design,fabrication and characterisation of microwave devices transistors and
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of the eukaryotic cytoskeleton and/or virology General proficiency in computing, including an understanding of high-performance computing clusters Downloading a copy of our Job Description Full details of the role
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the JOINER infrastructure. Evaluate the performance of developed solutions against benchmark decisions from existing tools. Extend the developed solutions to federated multi-slice environments for threat
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experimental medicine studies focusing on energy homeostasis and glucose/lipid homeostasis Data Collection & Analysis: Perform in vivo metabolic testing, blood sample and tissue analyses, and molecular biology
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cytometry will be an advantage. The project has a major computational component both for AI-driven modelling and predictions, and for bioinformatics analyses of wet-lab data. This will be performed by
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can be engineered to improve Rubisco's catalytic activity. The research programme will provide insight into direct molecular responses to carbon dioxide in prokaryotic and eukaryotic photosynthetic
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developing and implementing very large deep learning models. Familiarity with high performance computing environments (e.g., HPC clusters, GPUs, Cloud resources) and managing Linux based hardware systems