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Are you a researcher driven to understand and predict the fundamental mechanisms limiting lithium-ion battery performance? We are recruiting a Research Associate in Lithium-Ion Battery Modelling
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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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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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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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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | about 17 hours 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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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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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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these plants. The post-doc is expected to build upon existing in-house tools and, where applicable, enhance them by means of AI (machine learning) and data-driven methods. These models are aimed to support
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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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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 11 hours ago
traditional predictive attempts and limits the availability of training data for high-resolution atmospheric and hydrological models. This limitation is compounded by the fact that many atmospheric reanalysis