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Field
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the mechanistic modelling of pharmaceutical tablet disintegration. This UKRI/EPSRC-funded project offers a unique opportunity to join a dynamic research team collaborating with a consortium of academic and industry
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within and beyond the University. We are looking for a Research Fellow to research on the areas of Robotics and AI using advanced modeling and simulation. Key Responsibilities: Development of a quality
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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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experience in numerical modelling and analysis, particularly in optimisation and/or complex mechanical systems simulation, as well as having a solid understanding of aircraft design and aviation in general
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|2025/795 under the scope of the Project Machine Unlearning in Speech Foundation Models: Learning to Forget (LeaF), Refª 2024.14611.CMU , funded Fundação para a Ciência e a Tecnologia, I.P., is now
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responsibilities include: Optimising the aerodynamic performance of the PASTA reactor for airflow efficiency, sterilisation effectiveness, and noise reduction. Developing CFD models and validating results through
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experience in numerical modelling and analysis, particularly in optimisation and/or complex mechanical systems simulation, as well as having a solid understanding of aircraft design and aviation in general
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The role 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
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reinforcement learning, computational rationality and user modelling, and simulator-based inference. The post-holder will work on a project from Professor Kaski’s UKRI Turing AI World-Leading Fellowship. Research
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an integrated manner, taking into account the couplings between energy, water, and carbon exchanges in the envelopes. As part of the GREENVELOPES project, the TEB urban canopy model (Masson 2000, de Munck et al