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observations with hydraulic models and digital twins, new predictive tools can be developed to identify increasing failure risks and support proactive monitoring and maintenance strategies for drinking water
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on developing a new multi-disorder prediction approach that integrates different sources of information. You work with analytical model development, extensive simulation studies and analysis of existing large
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on the vision of developing multi-level thrombosis risk prediction models, from cellular dynamics to organ-level hemodynamics. The network integratesin silico, in vitro, and in vivo approaches to understand
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of digested humanure on soil. For the 100 most commonly prescribed pharmaceuticals in the Netherlands, their excretion profiles and their physico-chemical properties will be used to predict their persistance in
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for our environment? Will the streets ever by quiet again? This PhD will give you the opportunity to build models that predict this! Job description In 2023, global drone shipments reached 1 million
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manufacturing technologies and eager to develop and build experimental setups and combine this with physics-based modelling? Join us as a PhD candidate and contribute to making volumetric 3D printing predictable
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breeding programs and to support the reduction of methane emissions; a strong interest in statistical models, genomic prediction, and quantitative genetics, preferably with experience with one of more
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-learning (ML)- driven and physics-based computational workflows to screen large molecular libraries, predict key electrochemical and physicochemical properties, and deliver ranked shortlists of high[1
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-edge in silico, in vitro, and in vivo technologies to understand, predict and treat thrombosis? This is your chance!! Our goal: Develop multi-level thrombosis risk prediction models by integrating
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Job related to staff position within a Research Infrastructure? No Offer Description Do you want to be trained to develop multi-level thrombosis risk prediction models by integrating insights from