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Field
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breeding optimisation through design, and tritium separation technologies, among other aspects. This is performed using our state-of-the-art facilities at the University of Manchester, and with our National
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of designing, programming and validating a fully operational virtual-reality object-copying task that is ready for immediate deployment in experimental research along with access to, and experience of operating
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design. The role will combine experimental plasma science with numerical modelling to understand and improve nitrogen fixation pathways, alongside the use of analytical chemistry methods to quantify
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of next-generation materials for electromagnetic shielding applications. You will join a world leading group in materials discovery and will play a central role in the computational design and prediction
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, immersive design and visualization applied to cultural heritage/humanities research contexts. The postholder will participate in the activities of ‘Serious 3D in Art and Architectural History(Acronym
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emissions of networks through the use of carbon-aware network telemetry, and the implementation of new hardware support mechanisms. Your role will include the design, implementation and evaluation
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working towards a shared goal. You will be responsible for the design and pilot testing of machine learning-based automated ultrasound video analysis models that incorporate temporal reasoning. The research
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echocardiography dataset called CAIFE consisting of both healthy and abnormal fetal heart scans. You will be responsible for the design and testing of original machine-learning based methods for fetal heart
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research profile while accessing highly specialised facilities and expertise. Key responsibilities: Core research responsibilities Design, conduct and analyse laboratory experiments addressing the project’s
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to accelerate the translation of FLASH radiotherapy by designing and optimising a linear accelerator (linac) capable of producing megavoltage (MV) photon beams at ultra-high dose rates. The post is available