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with advanced analytics techniques such as predictive modelling and data mining. - Experience with artificial intelligence and machine learning applications in data analytics. - Proven leadership in
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interdisciplinary initiative focused on advancing Predictive, Preventive, Personalized, and Participatory (P4) approaches in health and medicine. Within the IRAP framework, the project’s scientific goal is to
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30th March 2026 Languages English English English The Department of Structural Engineering has a vacancy for Two PhD positions in “Micromechanics-based modelling of ductile failure in high-strength
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Position Information Position Information Working Title Manager, Biophysical Model Design (Temporary) Department Biochemistry-0831 Requisition Number S_260080 Posting Open Date 02/04/2026
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
microstructure evolution during extrusion is critical for controlling final mechanical properties and surface appearance of extruded profiles, yet quantitative predictions remain challenging due to the complexity
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, predict, and manage them remains fragmented across disciplines. The Understanding and Predicting Impacts of Climate Extremes under Global Change Doctoral Network (CLIMES DN) (https://www.climes.se/climesdn
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workflows that integrate modern AI and machine learning concepts (e.g., surrogate models, adaptive sampling strategies) into the drug discovery pipeline to increase throughput and predictive accuracy
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the Sustainability Institute at University College Cork. UCC invites applications for a Postdoctoral Researcher specialising in industrial decarbonisation modelling to support the EU-funded FLARE project. The role
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Centre de Mise en Forme des Matériaux (CEMEF) | Sophia Antipolis, Provence Alpes Cote d Azur | France | about 2 months ago
Automata (CAFE) to considerably reduce calculation times and improve the response of numerical models. The numerical models will include laser-matter interaction, melt, and microstructure prediction models
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results but are hampered by large individual differences in response. It is evident that we need to rethink the premises of randomized controlled trials (RCTs) to better predict who will benefit from which