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flexible hybrid onsite/remote working model, combining time at VIB headquarters in Ghent and academic groups at VIB’s Research Centers. A unique opportunity to help shape a cutting‑edge, AI‑driven biology
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flexible hybrid onsite/remote working model, combining time at VIB headquarters in Ghent and academic groups at VIB’s Research Centers. A unique opportunity to help shape a cutting‑edge, AI‑driven biology
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pioneering research in process systems engineering, with a focus on first principles and data-driven modeling, simulation and optimization with strong and permanent interactions with experiments. Integrate
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) Time series modeling, forecasting, and real-time monitoring in dynamic bioeconomic systems Data-driven modeling and intelligent control in bioeconomic systems Out-of-distribution (OOD) generalization in
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on the track of Cyber-Human Physical Systems seeks researchers to advance Systems Science and Engineering by modeling human behavior in complex dynamic networks addressing global challenges. Emphasizing Cyber
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description he project aims to develop a data-driven model to
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and data-driven modelling approaches in representing quality degradation and shelf-life dynamics. Exploratory perspectives on how digital technologies and data-oriented analyses may inform scientific
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the production of spatially granular and engineering driven representations of model results. Experience working across disciplines in multi-institution and multi-stakeholder collaborations is desirable
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multimodal generative AI for music/audio. Check out some of our recent projects here: https://dorienherremans.com/biblio (including work on models like Mustango, SonicMaster and other generative systems
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 4 days ago
conditions: Scientific area: Bachelor’s Degree in Systems Engineering. Work plan: Model-based digital twins supported by physics-informed machine learning for multiphysics modeling. 1. Grant duration and