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level of detail extracted from these experiments. As part of this role, you will work closely with other researchers to translate these experimental results into our numerical models, helping to improve
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researchers to translate these experimental results into our numerical models, helping to improve their predictive capability. You will help ensure a healthy and vibrant research environment within the Impact
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The post holder will develop computational models of learning processes in cortical networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly
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(LiB’s). You will be responsible for: • Developing models and simulations of the electrode fabrication process, sensors, and actuators. • Developing a demonstrator of a soft sensing system that
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. Concurrently, you will develop lower order analytical models and perform high fidelity computational simulations to corroborate experimental findings and propose other configurations to be subsequently
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). The post is funded by NIHR and is fixed-term for 24 months, with a possible extension. This project is about creating novel AI models to predict patient outcomes following acceptance or refusal of an offer
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of original machine-learning based algorithms and models for multi-modal ultrasound guidance that are intuitive for a non-specialist to use while scanning and trustworthy. You will work with clinical domain
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microscopy, as well as in developing approaches to track cell migration in the spleen in real time. Extensive experience with immunization and infection models is also essential. Experience in independently
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of 24 months. The project aim’s to develop new constitutive models to describe the mechanical behaviour of Thermoplastic Elastomers (TPEs). These polymers are increasingly being developed as a