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prospective students about the programme; determining and aligning admission criteria for the Master's programme, assessing applications and admission of students to the Master's or Pre-Master's programme
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of infrastructure components (e.g., pavement stones, concrete kerbs, sewage pipes) is gaining momentum, but scaling remains difficult: supply and demand rarely align in time, place, and specification, and
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. These coating materials are tested in the laboratory but their performance does not always align with field observations. Within this project, we strive to close the gap between laboratory test campaigns and
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to identify multiple diseases using one blood sample or medical image. These tests can find diseases early, before symptoms develop. However, they often produce false positives, indicating disease when none is
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multiple brain areas in an optimised way. This may include neural network and neural mass modelling of large-scale brain activity during and after stimulation, and experimental tACS in healthy participants
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and guidelines for scalable, circular manufacturing systems across multiple industrial sectors. 3. Material Selection for Durable and Circular Additive Manufacturing: This PhD project focuses
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bridging digital modelling with real-world factory implementation, this project will contribute practical methodologies and guidelines for scalable, circular manufacturing systems across multiple industrial
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specific end date to this vacancy, since it concerns multiple positions that has become available. For more information about this open vacancy, please contact our secretary Mrs. Jacqueline Kroese via