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geoscience, energy systems, materials modelling, fluid dynamics, and other scientific and engineering domains where data-driven models must interact with physical knowledge. Such problems raise fundamental
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” modeling solutions; we are open to and excited about applying all different types of statistical and ML techniques, from linear models to deep learning, depending on what best fits a given problem. The most
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In this PhD position, you will help design the next generation of circular plastics systems by combining hands-on polymer processing with data-driven modelling. The PhD study is a full-time, fixed
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-year research and innovation programme developing next-generation circular steels that can safely operate in hydrogen environments. By combining advanced experiments with multiscale modelling, CIRHY aims
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The overall aim of this PhD project is to understand the influence of climate-driven changes in vegetation cover and winter conditions on habitats and food webs of Arctic/alpine lakes. Climate change is
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for entry into a PhD program. A background in machine learning, inverse problems, scientific computing, or related data-driven methods is highly desirable. You are curious about combining physical modeling
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combining advanced experiments with multiscale modelling, CIRHY enables reliable, sustainable steels for future infrastructure and industry. The project was granted by the Dutch national funding agency NWO in
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the influence of climate-driven changes in vegetation cover and winter conditions on habitats and food webs of Arctic/alpine lakes. Climate change is promoting the expansion of terrestrial vegetation, which
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hydrogen environments. By combining advanced experiments with multiscale modelling, CIRHY aims to enable reliable and sustainable steels for future hydrogen infrastructure and industry. Hydrogen
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-driven, and grounded-on-Country initiative introduces a transformative model of care that integrates ancient cultural wisdom with modern neuroscience and digital innovation—addressing long-standing health