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breeding programs and to support the reduction of methane emissions; a strong interest in statistical models, genomic prediction, and quantitative genetics, preferably with experience with one of more
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for Predictive Product Properties (MTV)". Your research focuses on the experimental and material-modelling foundations required to enable predictive and controlled TVAM. You will be embedded in the Processing
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cutting-edge microfluidic experiments with advanced numerical modeling. Your work will enable upscaling from pore- to column-scale clay behaviour under real-world conditions relevant to sustainable
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, support decision-makers, and advance debris-flow modelling for future research. In this PhD, you will carry out field measurements and run numerical simulations to better understand and predict debris-flow
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. This in turn, will place a biologically important process into global carbon cycle models and thereby improve predictions of the consequences of ongoing CO2 emissions. YOUR ROLE Within this project, you
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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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sources, and that the operations must be less predictable in their chosen transport means and locations. Thus, the goal is to explore reduced predictability while sustaining the units to be supplied
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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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environment, including tasks such as calculating sample compositions. A quantitative mindset with the ability to analyse data, make predictions, and perform back-of-the-envelope calculations. Mindset and
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of adolescents. How is their mood affected by sleep (deprivation), social media, music and role models? Toenders' research is unique in that she not only views adolescents as research subjects but also involves