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Field
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, and you work in a structured and focused way; experience in (plant) molecular biology approaches; experience with experimental research on seeds is an advantage; enthusiasm for working in a team and
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describe ecosystem structure and functioning as a function of size and other relevant properties. You will test the theoretical framework developed on empirical data currently collected independently in
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how trust interacts with (structural) governance principles, ecosystem properties, and stakeholder expectations/behaviour, amongst others. You will map ecosystems relationships through trust mapping and
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security-oriented workflows. This includes designing methodologies that ensure traceability, robustness and bias mitigation in AI models, as well as creating prototype tools that demonstrate how transparent
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that structural neglect through an interdisciplinary, participatory research program that combines empirical research, legal and policy analysis, and technology assessment. Grounded in a Theory of Change approach
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of society. These include institutional transformations in governance, coordination, and economic systems; shifts in social and relational structures; and changes in shared frameworks of meaning that shape
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characterization techniques, particularly solid-state NMR and X-ray/neutron scattering techniques for the investigation of structure-property relationships in battery materials. Strong background in battery research
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are the agriculture sector, construction sector, asphalt paving sector, aviation sector, and household sector. In particular, you will try to understand what the theoretical and actual policy bottlenecks are at local
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, medical imaging, pathology, molecular biology, and biostatistics. The resulting international biobank of precisely characterised tumour samples provides the basis for countless research projects and opens
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real-to-sim-to-real pipelines that automatically construct simulation environments from video recordings or images of real-world robotic tasks, enabling scalable and low-cost training data generation