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approach, we crowdsource and co-create scalable climate education and communication methods and evaluate their effects in educational settings. In this position you will be responsible for co-designing
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mathematics (or closely related discipline) is a requirement by the start of the position. Enthusiasm for topics in probabilistic and extremal combinatorics and/or structural graph theory. Prior experience in
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-on experiments to answer a question that matters for biodiversity conservation? If so, this PhD-position could be the perfect fit for you! Human-driven nitrogen (N) deposition is changing ecosystems worldwide. It
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to interdisciplinary research that supports transitions towards more sustainable farming systems? Then we would love to hear from you. We are looking for a candidate with experience in the governance of farming systems
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of this sustainable approach. In addition, you will contribute to the scientific basis of the Nature Restoration Plan and the management plans for Natura 2000 sites in the South-Western Delta. Liaising with clients and
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the 36 months immediately before their recruitment date. Where to apply Website https://www.academictransfer.com/en/jobs/364130/phd-vacancy-knowledge-creation-… Requirements Specific Requirements Your
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-year research and innovation programme developing next-generation circular steels that can safely operate in hydrogen environments. By combining advanced experiments with multiscale modelling, CIRHY aims
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classification of aluminium scraps and contaminants. Design and validate algorithms for multi-sensor data interpretation and sensor fusion. Conduct laboratory experiments on scrap characterisation and sorting
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/Euregion business and innovation community. An entrepreneurial, outward-facing mindset — as comfortable building partnerships outside the university as teaching inside it. Interest in or experience with agri
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Civil Engineering, Mechanical, Electrical, or a closely related field. Demonstrated expertise in ESM and IAM. Experience with High Performance Computing (HPC) and large-scale dataset analysis. Strong