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takes place both in natural areas and working landscapes. However, little is known about where and what conditions enable nature restoration projects to be successfully implemented. In areas with high
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temporal scales from seconds to hours and beyond. The aim of this PhD project is to build a multi-scale model linking molecular renewal to functional properties of synapses to study the relationship between
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approaches to quantify the impact of changing environmental conditions on maintenance strategies, operational risk, and long-term O&M costs. The project will ultimately provide insights that help offshore wind
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1 Research fellowship for MSc (BI), to a PhD student or MSc enrolled in a non-academic degree course
enrolled in a non-academic degree course, within the Research Project entitled “Polymer-IR780 conjugate based Tetrazine-Norbornene click injectable in situ forming hydrogels: fine-tuning the polymer
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of Sport, Exercise, and Nutrition Education – kimberley.edwards@nottingham.ac.uk This project is not funded, and we are seeking a student who can self-fund the PhD. Programme description: Athletes, coaches
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University of Medicine and Pharmacy organizes an open for the appointment within the project PN-IV-P2-2.1-TE-2023-1890 entitled “A texture analysis practical framework for the development of nanotechnology
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Agreement pay scale. Contract type: Technical and scientific activities contract linked to project activities. What can we offer? Incorporation into the Vall d’Hebron Research Institute (VHIR), a public
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we’re growing along with it. At the Universiteit Maastricht (UM), your work makes a difference—whether you explore complex biological systems, contribute to cutting-edge research, or help shape
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international conferences; assisting with activities to disseminate the project's findings both within and outside the academic world; publishing peer-reviewed articles and book chapters. Your qualities You are a
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into answering counterfactual questions. Using remote sensing multimodal time-series data and Earth foundation model embeddings, you will design and develop causal machine learning models tailored for dynamic