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mechanics at the atomic scale. In this project, the University of Groningen will develop an array of state-of-the-art machine learning potentials for multi-component alloy systems that are relevant
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Engineering, Computational Physics, Materials Science or a related discipline is required, with experience in atomistic modelling of materials and machine learning. Experience in atomistic modelling (molecular
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-GUIDE project, we will make directed evolution guidable and, ultimately, predictable by machine learning. Specifically, you will build a first-in-class framework to expedite the design of high-affinity
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of the Open Competition Domain Science-M programme (Twenty-one innovative research projects awarded through Open Competition Domain Science-M programme | NWO - https://www.nwo.nl/en/news/twenty-one-innovative
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inventory, a major incentive for the project is the application and adaptation of state-of-the art machine learning codes to deal with redshift distortions, intrinsic (galaxy) biases, survey selection biases
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, ultimately, predictable by machine learning. Specifically, you will build a first-in-class framework to expedite the design of high-affinity binders that engage with therapeutic targets or efficient (bio
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adaptation of state-of-the art machine learning codes to deal with redshift distortions, intrinsic (galaxy) biases, survey selection biases and in particular the complications encountered in photometric
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dedicated Master's program in Ecology and Evolution that offers extensive fieldwork opportunities. Furthermore, the university-wide Rudolf Agricola School for Sustainable Development engages FSE members in
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learning environments based on pedagogies that promote justice and fairness. To address this need, the Centre for Learning and Teaching (CLT) is offering a fully funded, 4-year PhD. The selected candidate
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for this position will have the following qualifications/qualities An MSc degree in chemistry or a related field. Very strong academic performance. Experience in molecular machine learning. Experience with