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properties of catalysts together with statistical methods to derive predictive models for selective catalysis. In a data-driven approach, an initial set of reactions is analyzed and used to establish such a
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Vacancies PhD Candidate Geospatial Risk Modelling for Climate Finance Key takeaways Effectively understanding and mitigating financial risks associated with climate change is important for
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), sustainable, and climate-adaptive crops. By combining plant biology, simulation modelling, and artificial intelligence we aim to develop smart breeding and cultivation methods. Thus, we try to speed up
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) developing and validating preprocessing pipelines; (3) architecting and comparing spectral-only and multimodal (HSI + NIR + Raman + RGB) deep-learning models; (4) implementing robust sensor-fusion strategies
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to train an AI model that predicts the cis-regulatory code for synthetic genomes (i.e. for cell-free gene expression systems) and correlates the experimental conditions within the synthetic cell
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attendance to two Dutch Research Schooles in Theoretical Physics over the course of the PhD. The position is embedded in a vibrant community of theoretical cosmology, gravitational-wave, and string theory
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on addressing the complexity of the device-software-application-data design space, enabling systematic and efficient exploration using modeling and simulation tools.## Key Responsibilities- Identify and
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: 30 August 2025 Apply now As part of the EMBRACER project external link , you will use advanced models integrating our climate system to human behaviour to study potential scenarios of what could happen
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models combined with the finite element method. Constitutive relations are required to describe material behavior. Advanced stainless steel typically possess complex microstructures across various length
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gyre (SPG) and Arctic and Antarctic sea ice cover, involving processes on smaller scales, which are often not well represented in modelling efforts focusing on the large scale tipping elements