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Postdoc: Hybrid Geospatial Modelling and Scenario Development of Biomass Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 32 to 40 Application deadline
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science across experimental models and imaging modalities. The Delft work is placed in the microscopy innovation node, with biological collaborators at Utrecht University (prof. Lukas Kapitein) and Erasmus
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multimodal deep learning models that integrate imaging and clinical data to personalize treatment and follow-up strategies. In the Netherlands, around 75% of patients with an abdominal aortic aneurysm (AAA
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to create smart, sustainable, and equitable mobility systems. In our 12 collaborative labs we apply advanced technologies such as sensing, data analytics, modelling, and AI to turn scientific research
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their involvement in disease resistance under controlled conditions. Our model system is the bacterial pathogen Xanthomonas campestris pv. campestris (Xcc), which causes black rot disease in cabbage
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disruptions in support systems affect access to and quality of care. The findings will inform new data, models, and policy recommendations, contributing to both Dutch and international debates on health system
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data, models, and policy recommendations, contributing to both Dutch and international debates on health system resilience, climate adaptation, and health equity. Your role will be to: Map current
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Bring segregation theory and models to industrial practise. Job
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with analysis of proteomics data is essential. You are highly motivated, creative and willing to work with human postmortem brain tissue and Parkinson model systems. Within this project most
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select a technique adaptable in the laboratory scale environment for further experimental work. Design and perform lab-scale experiments in the laboratories at TU Delft. Develop a mathematical model