18 machine-learning "https:" "https:" "https:" "https:" positions at University of Bristol
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technologies using novel hardware accelerators, and the development of fast simulations using generative machine learning techniques. Depending on the successful candidate’s experience and track record in
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The Atmospheric Chemistry Research Group (ACRG) and School of Engineering Mathematics at the University of Bristol have developed GATES, a graph neural network (GNN) machine learning model that can
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development and capacity-building initiatives. You hold a PhD in immersive technologies or related fields (e.g., VR/AR/MR/XR, HCI, AI for XR, computer graphics). You have proven ability to teach at a high
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an advanced data fusion and machine learning pipeline that measures changes in specific mobility-related behaviours over time. Thus, TORUS will create the capability to autonomously, continuously and
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machine learning techniques to address new research challenges (ideally with track record in distributed/federated AI or embedded neural networks). •You have a track record in one or more of the following
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machine learning (ML) and AI across our Aero, Civil, and Design programmes, all ranked in the UK’s top five. If you’re passionate about advancing engineering science through AI and eager to collaborate with
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machine learning (ML) and AI across our existing Aero, Civil and Design programmes, all of which are ranked in the top 5 nationally. If you are passionate about pushing the boundaries of engineering science
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using CAD which combined large-scale cellular simulations and machine learning (unpublished data). These modelled cells demonstrated significantly boosted metabolic production, and we are aiming to prove