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Field
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, you will focus on developing mathematical models and numerical algorithms that systematically integrate uncertainties into the design process of optical systems. The goal is to enable novel design
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will develop and explore the potential of farm typologies to deal with heterogeneity and tailor a nature-inclusive transition; explore the diverse values of nature among diverse stakeholders; and co
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wave equations. In the project, we will develop a new mathematical and computational framework that combines PDE-based modelling with ideas from data-driven reduced-order modelling. The aim is to obtain
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’ preferences in terms of ‘productive agriculture’ and ‘healthy biodiversity’ into quantifiable impact indicators; Develop a spatial optimization algorithm that finds land use configurations that optimize
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responsibilities: Prepare, organize, and participate in multi-week fieldwork expeditions; Collect, preserve and analyze field samples; Analyze large data sets; Publish and present the results in scientific
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, you will: Acquire and analyse human neuroimaging data, with a primary focus on high-field fMRI of natural sound perception. Develop and apply AI/NeuroAI models, including deep neural networks, to model
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plants in the automated phenotyping facilities of the Netherlands Plant Eco-phenotyping Centre (NPEC) . Using high-resolution imaging, you will follow plant growth, physiology and disease development after
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conduct studies in collaboration with primary schools and educational partners, review the scientific literature, recruit and test participants, develop and evaluate educational materials and experimental
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You will join t he Decision, Development and Psychopathology (D2P2) lab and your supervisory team will consist of Bernd Figner, Kim Fairley (both Radboud University), Kirsten Rohde (Maastricht
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such as publication and patent data, and aims to enrich these with other sources on individual paths and preferences. The PhD candidate will have the opportunity to develop unique datasets and apply