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Vacancies PhD Position: Improved Temper Roll-Force Prediction Through Microstructural Modelling Key takeaways Steel is extensively used in sheet form across a wide range of applications. Two
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a dissertation? In that case, the position of PhD Predicting and Decision-making at the University of Groningen (UG) might just be what you are looking for! As a PhD candidate in prediction and
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Apply now In this MICROP project, we aim to develop predictive AI models to decode plant–microbiota host specificity, with the ultimate goal of forecasting the success of microbial introductions—ranging
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are essential to the biological function of all organisms. For example, haemoglobin must change conformation to bind oxygen and fulfil its biological function. While machine learning approaches that predict
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schools see the weaknesses in their school environment and predict the effect of possible interventions to improve the environment. In this position, you will collaborate closely with another PhD student
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properties of catalysts together with statistical methods to derive predictive models for selective catalysis. In a data-driven approach, an initial set of reactions is analyzed and used to establish such a
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trends. Data-driven approaches are attractive alternatives. Descriptors are used to characterize the molecular properties of catalysts together with statistical methods to derive predictive models
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-LYNCH (‘Validated non-invasive liquid biopsy tests for cancer PREDIction in LYNCH Syndrome’) which brings together contributors from many countries and with different types of expertise. Therefore, you
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materials, to aid design of novel more energy-efficient processing routes. The development of these digital twins requires reliable and predictive models for microstructure formation during steel processing
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of these digital twins requires reliable and predictive models for microstructure formation during steel processing. These models should be based on accurate predictions of phase stability and defect kinetics