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in Germany, to create powerful THz receivers. This outcome will not only create a step change in signal-to-noise performance but will allow scaling of the sensors to create multielement arrays
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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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: Qualifications A good first degree in an Engineering related subject. A PhD (or be close to submission) in Marine, Mechanical, Thermal Engineering or Computer Science. Experience Experience in conducting high
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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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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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appliances, such as TVs, fridges, enable researchers to investigate demand-side management strategies, energy efficiency measures, and innovative energy-saving solutions; · High-performance computing
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and modelling of nanoelectronic devices operating at cryogenic temperatures (4 Kelvin - 77 Kelvin) for energy efficient quantum computing (QC) and high-performance AI computing in data centres
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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
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About us The Faculty of Natural, Mathematical & Engineering Sciences (NMES) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics – all departments highly rated in research
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Trust Career Development award funded research programme “Unlocking the RNA Helicase Code: From Structural Insights to Therapeutic Strategies” led by Dr. Jagtap. The overall project builds upon our novel