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topics: a) introduction of highly efficient DGL models to reduce the energy impact and increase the sustainability of DGL models; b) increase the expressiveness of DGL models, obtaining better predictive
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. Generate, curate, and augment training datasets using FEFF-based simulations and experimental data. Conduct beamline experiments to validate model predictions and integrate them into real-time analysis
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Research Infrastructure? No Offer Description Mission: Support the design, training and validation of temporal models aimed at detecting ecological patterns and predicting events such as the bloom of Oceanic
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attention to scientific rigor and interpretability Experience with XAI tools (SHAP, LIME, Integrated Gradients) to identify which features of the model are driving the predictions Clear written and verbal
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
physics- and data-driven models that deal with microstructure/texture evolution during extrusion to predict material properties of extruded profiles Collaborate with other researchers and industry partners
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the integration of behavioural data with AI. The student will analyse eye movements, exploration patterns, and verbal reports to develop computational models that predict identification reliability
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data to identify proteomic signatures and develop novel predictive models for Alzheimer’s, Parkinson, and Dystonia as well as to identify novel proteins and pathways implicated on disease pathogenesis
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require additional information? Please contact: Efstratios Gavves, Associate Professor, e.gavves@uva.n Where to apply Website https://www.academictransfer.com/en/jobs/359154/postdoc-on-robot-world-models-u
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, advanced studies, specialized training). Preferential factors: Professional or academic experience in Machine Learning; Professional or academic experience in Finite Element Modelling; English language
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Overall, Purpose of the Job The main tasks are to advance the use of high-fidelity modelling to improve understanding of the characteristics of the turbulent wakes that develop downstream of large