459 model-driven-development "Integreat Norwegian Centre for Knowledge driven Machine Learning" PhD positions in Netherlands
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Are you intrigued by the potential of light-driven chemistry to create sustainable, bio-based polymers? Are you passionate about developing innovative recycling technologies that support a more
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for the current climate is developed using hydraulic models. These scenarios describe the consequences of a flood in terms of flood depth, flood extend, economic damage and loss of life. These scenarios
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? We are looking for a PhD candidate to develop AI methods that extend current sets of flood scenarios derived from physical and numerical models, incorporate climate change effects, and then use
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at the interface of biophysical modeling, soft matter and cell mechanobiology at the Groningen Research Institute of Pharmacy, within the Faculty of Science and Engineering at the University of Groningen. What
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Develop advanced models to understand and predict piping
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to develop engineering interventions to improve plant regeneration, seed longevity and defenses against disease. Your task will be to further develop two-dimensional and three-dimensional models of plant
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Develop advanced models to understand and predict piping and internal erosion in dikes. As a PhD researcher at TU Delft, you will connect fundamental fluid–soil interaction physics with
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multiscale simulations and AI predict how a breathable material knows when to seal? In this PhD project, you will develop responsive MOF-peptide coatings for adaptive surface functionalization and derive
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white matter. The network aims to strengthen the full translational pathway, from understanding disease mechanisms and developing disease models to preclinical therapy testing, clinical readiness and
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and economic use of renewable electricity without an unnecessary discarding of generated power. This four year’s PhD position is aimed at developing multiphase models to predict the dynamics and