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Are you an engineering scientist who wishes to contribute to high-tech applications, state-of-the-art modelling or experimentation of advanced sustainable materials across the scales? We are looking
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remain resilient in a world of increasing climate uncertainty? This PhD project offers the opportunity to work at the intersection of climate change, food systems, and advanced optimization modelling. You
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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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estimated from observed data. The overall aim of the project is to develop statistical theory, methodology, and computational methods for such complex data problems, with a particular focus on models
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predictive modelling. The project gives you the opportunity to work across scales: from thousands of plants and complex microbiome datasets to mechanistic experiments with individual microbial isolates. Your
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develop AI tools for the interrogation of subcellular proteomics data. We are interested to hear from candidates with experience in probabilistic or statistical modelling of complex biological data, such as
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Welcome to Maastricht University! How does the human brain transform complex natural sounds into meaningful percepts, and can artificial neural networks help us understand this process? Join the
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domains where data cannot be directly shared, such as healthcare and finance, the ability to selectively remove the influence of specific data from trained models becomes critical. Yet, despite the EU’s
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the complex microstructures of circular steels and causes degradation and failure. This position is part of the project "Circularity as Opportunity: Engineering Hydrogen-Resistant Circular Steels (CIRHY)", a 6
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Primary Supervisor: Dr Jonathan Kirby Model theory is traditionally done with “classical first-order logic”, the logic which allows unlimited use of the operators AND, OR, NOT, with the EXISTS and