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suited for a provided data set and scientific question. In practice, statistical models contain many arbitrary choices that may (a) have a detrimental effect on what we can learn from it and (b) greatly
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from largely unlabelled data that can generalize across different radar configurations and be efficiently adapted to multiple downstream perception tasks with limited labelled data. An important research
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risk management. Reliable numerical models can improve our understanding of how piping develops and help engineers assess and design safer, more reliable flood defence systems. In this PhD project, you
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-vertex graphs as induced subgraph?'), reconstruction problems ('How many distances are required to reconstruct the edge set of a graph?') or finding structures that can lead to faster algorithms ('How fast
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. In this PhD project, you will investigate foundation models for automotive imaging radar. The goal is to learn general radar representations from largely unlabelled data that can generalize across
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extra vacation days. Through the UU Terms of Employment Options Model, you can tailor your employment package to your needs. This way, we encourage you to grow in what you do, both in your work and your
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ingredients, a process that is traditionally slow because each substrate–strain combination behaves differently. By applying machine learning to historical experimental data, we can predict high‑potential
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measurable. This can be approached through empirical analysis of large-scale simulations, through new (semi-analytical) models that predict the impact of introducing these vehicle types, or a combination of
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the project "Circularity as Opportunity: Engineering Hydrogen-Resistant Circular Steels (CIRHY)", a 6-year research and innovation programme developing next-generation circular steels that can safely operate in
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project developing next-generation circular steels that can safely operate in hydrogen environments. By combining advanced experiments with multiscale modelling, CIRHY enables reliable, sustainable steels