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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in the prediction and modelling of extreme flood events? Do you want to understand how
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these challenges by: Developing predictive workload, lead-time estimation, material planning models to capture the high variability in HMLV environments using hybrid AI (combining machine learning, feature-based
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, thus achieving a vascular model with a broad range of (relevant) dimensions. To connect the chips to a perfusion pump, it must be contained in a small casing which should be made from materials
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for Technology-Inspired Regenerative Medicine (http://merln.maastrichtuniversity.nl/) as part of the DRIVE-RM project. The computational group led by Aurélie Carlier focuses on multiscale computational modelling
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varying material properties. The resulting response will be analyzed using techniques such as Monte Carlo simulations. Identifying the variability of the model parameters using Bayesian inference
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energy research. Responsibilities Develop and implement machine learning models to analyze and predict materials properties and performance trends from high-throughput experimental data. Design and
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models to analyze multimodal video data (facial expressions, tone, behavior, and speech) for dynamic wellbeing assessment. You will work with open-source datasets as well as video material from
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. Your results will support cross-moon comparisons and help decode JWST’s spatial and spectral variations. PhD 3 | Ocean–surface transport modelling You will model how ocean material is transported through
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modelling. Its research themes include the ageing and healing of asphalt materials, the development of low-temperature and recycled mixtures, rejuvenation and circularity concepts, and the multi-scale
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the crystalline anisotropy in the particle-continuum formulation The modelling framework above will strongly depend on experimental input for the material characterization and validation. The interaction between