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integrating machine learning and domain-specific knowledge to predict failure arising from hydrogen embrittlement. You will carry out materials testing, computational model development, data processing, and
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highly motivated doctoral student to join an ambitious project aimed at building machine and deep learning models to study the genetics of human disease. Funded as part of the Helmholtz AI program, the
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innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools
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: Develop innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry
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of the behavior of machine elements • Development and validation of physically based models for the prediction of wear and damage • Publications at international conferences and in scientific publications. Your
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with high-dimensional, often noisy, data sets; and mathematical modelling approaches that reduce the dimensionality of parameter spaces and produce mechanistically realistic, experimentally testable
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applied in Africa’s livestock sector. This work will involve modelling analyses using methodologies to be developed by the candidate in collaboration with their supervisors. This is one of two positions