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behaviour through these models using uncertainty quantification/machine-learning (UQ/ML) algorithms To optimise the manufacturing process with the help of the simulation tool To support in the development and
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facilities and competences covering the whole chain of manufacturing, characterization, mechanical testing and modelling of fibre composites. Responsibilities and qualifications Do you have a strong research
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We’re seeking for motivated candidates that are interested in developing computer models of the composite human neuro-muscular system that combine detailed musculoskeletal geometries, muscle-tendon
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dynamics resulting from varying compositions. An adaptive Model Predictive Control strategy is envisaged for this challenge. During the four-year doctoral programme, you will contribute to the group's R&D
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
Thermography. This raw dataset is needed to be processed and annotated to train supervised and unsupervised AI models. The research will aim to develop deep learning algorithms for damage classification
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that are interested in developing computer models of the composite human neuro-muscular system that combine detailed musculoskeletal geometries, muscle-tendon models and neural control pathways (e.g., CPG-like and
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seeking for motivated candidates that are interested in developing computer models of the composite human neuro-muscular system that combine detailed musculoskeletal geometries, muscle-tendon models and
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mechanisms, namely the remodelling of membrane lipids. Lipid remodelling is a process whereby bacteria selectively modify their membrane lipid composition in response to a particular environmental stimulus
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variations in the chemical composition of the steel produced, which may affect the performance of the steels during processing and service. This is particularly true for stainless steels undergoing phase
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composites. Position 1 – Ply and blank bending during hot press forming Wrinkling is one of the primary process-induced defects in press-formed thermoplastic composite parts. Predicting wrinkling requires