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and have access to state-of-the-art industry experts, data and knowledge, allowing you to make an impact during your PhD research. In this position you will work with real world data and models, aimed
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the breeding of complex resilience traits for several crops in different growing systems. This collaborative effort involves four universities and numerous companies. It encompasses scientific research, data
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for the new green steels compositions, including impurities and tramp elements. These models should enable density-functional-theory (DFT) accurate large scale atomistic simulations of defects including
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density-functional-theory (DFT) accurate large scale atomistic simulations of defects including dislocations, grain boundaries and precipitates, as well as phase diagrams exploration. A key challenge faced
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we deal with are relevant to everyone around the world and Wageningen, therefore, has a large international community and a lot to offer to international employees. Because we expect you to work and
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the weblike distribution of galaxies in large galaxy redshift surveys, with the corresponding velocity flows inferred from measured galaxy peculiar velocities. These measurements are to be converted into a
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the increased size and heterogeneity of such systems, which typically comprise a large number of distinct but interacting components. To address these challenges, this project aims to contribute
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including the active exchange of data and results, regular team meetings, and integrative analyses. You will be supervised by a team of scientists from Naturalis and NIOZ. Training and courses during the PhD
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-property relationships are rare, providing a large open catalyst space to be explored. This project will rely on data-driven workflows for the closed-loop design of ligands that will facilitate challenging
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in these reactions is still rather limited and comprehensive structure-property relationships are rare, providing a large open catalyst space to be explored. This project will rely on data-driven