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on the integration of BIM, artificial intelligence and predictive maintenance (PM) for intelligent BIM models, digital construction sites, predictive analysis and immersive interactions, outlining an operating
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and knee, conducted at Imperial College, before creating new subject-specific models using a forward-dynamics approach to predict the effect of variation in hip muscle strength on the iliotibial band
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molecular simulations, and cutting-edge AI techniques including graph neural networks (GNNs) and large language models (LLMs) to accelerate experimental design and discovery of novel materials. The research
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applied in particular to the modeling of 3D-printed concrete at the Navier laboratory, to better predict complex phenomena such as material curing and crack formation. Where to apply E-mail jeremy.bleyer
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modelling predictions. Experience or a strong interest in scientific programming and machine-learning-assisted data analysis for materials modelling is an advantage. PhD Position 2 – Coarse-Grained and
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-edge in silico, in vitro, and in vivo technologies to understand, predict and treat thrombosis? This is your chance!! Our goal: Develop multi-level thrombosis risk prediction models by integrating
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) processes within the EIC PATHFINDER project PREDICT by unifying detailed physical models - light transport, surface reaction kinetics, and multiphase reactive flows - into a single CFD framework. The goal is
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biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run high-performance numerical experiments
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, artificial intelligence, and critical infrastructure protection. Research Topics The PhD research will focus on one or more of the following areas: Detecting, predicting, and preventing hybrid and cyber
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Job related to staff position within a Research Infrastructure? No Offer Description Do you want to be trained to develop multi-level thrombosis risk prediction models by integrating insights from