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, RNAseq, serum proteome, WSI), incorporating the clinical data, primarily for the identification of biomarkers that predict response to treatment. The spatial studies will be a key focus, but integration
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Helmholtz-Zentrum für Infektionsforschung GmbH | Braunschweig, Niedersachsen | Germany | 29 days ago
Description The department EPID, led by Prof. Berit Lange, at the Helmholtz Centre for Infection Research (HZI), isoffering the position of a Doctoral researcher (f/m/d) Modelling vector-borne diseases in
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Project This project aims to develop the Amazonian Early Warning System (AmEWS) - a near real time, data- and model-driven platform that focuses on multi-hazard risk prediction for the Amazon rainforest
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to study and predict. In this four-year SNF-funded project, you will develop data-driven, multiscale simulation methods that combine computer simulations, machine learning, and surrogate models to explore
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characterised and used to train and validate ML models that link synthesis conditions to performance metrics, enabling predictive optimisation of aerogel-based supercapacitors. The project will be undertaken
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-scale brain imaging datasets of responses to images and model these representations with computational models and validate these predictions in follow-up neuroimaging experiments, Define and model
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | about 1 month ago
to intertwine a multi-contact whole-body controller, a digital simulation of the interacting humans, and machine learning models to predict and respond to human movements and intentions. In a crescendo of
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on building dynamic system models for both the energy conversion technologies and the greenhouse climate, integrating these into a unified framework suitable for state estimation, predictive control, and
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to effectively train AI models based on limited and imprecise information as well as unbalanced and heterogeneous multimodal data. This needs-driven method development finds direct application in healthcare
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macro- scales at IJL, and to train machine learning models to predict the microstructure evolution at larger scales and longer times at SIMAP lab and Laboratoire Analyse et Modélisation pour la Biologie