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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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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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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 10 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
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of the Foundation for Science and Technology, I.P. (model below, for student enrolled in a non-academic degree course integrated in the educational project of a higher education institution, developed in association
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. Experience with advanced analytics, including predictive modeling, data science, or statistical analysis to support data-driven decision-making. Demonstrated experience designing and implementing ETL/ELT
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and innovation. ERIK positions Ohio State to expand curiosity-driven research and creative expression, further develop our research community of faculty, staff, and students, and grow the innovation
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25 Feb 2026 Job Information Organisation/Company UNIVERSIDAD POLITECNICA DE MADRID Department HRS4R Research Field Engineering » Civil engineering Researcher Profile First Stage Researcher (R1
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into reliable information about structural and aerodynamic behaviour remains a challenge. The PhD will develop data-driven methods that combine measurements, physics-based models, and machine learning to extract
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(SustainCARE, https://doi.org/10.3030/101220359 ), led by Dr. Yun Liu. SustainCARE brings together heritage science, building physics, advanced modelling, and climate-conscious preservation, offering a unique
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of interactive web-based and/or immersive analytics environments that integrate temporal networks, heterogeneous spatial-temporal data, and AI-driven forecasting and simulation models. These environments will