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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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The project: Non-destructive testing (NDT) is vital to ensure structures are safe and to reduce operating costs by facilitating predictive maintenance. The focus of this project is on improving
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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
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project involves interdisciplinary research at the interface of computer science and mathematics, with a focus on bivariate molecular machine learning for modeling molecular interactions and properties
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and difficult to anticipate. Predicting the spatio-temporal dynamics of these changes generally relies on empirical models, most of which project correlational relationships between species occurrences
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close coordination with project partners, the recruited researcher will conduct experiments to determine the extent to which neural models, now at the heart of many approaches to Natural
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, creating predictive models for failure control. Validation & Experimental Collaboration: Compare simulations with experiments, collaborate on proof-of-concept testing, and refine models based on results
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comfort throughout the year in a Nordic climate? Is it possible to predict dynamic outdoor thermal comfort with sufficient accuracy using fast parametric algorithms and machine learning (ML) models instead
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prediction, focusing on efficient edge deployment (e.g., through model pruning, quantization, or TinyML techniques). The embedded system will be designed to perform local inference in real-time, minimizing