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acceptability. D2ET will develop a comprehensive digital platform for planning energy transition scenarios, leveraging a consolidated data model and advanced analytics to facilitate strategic decisions with
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, a state-of-the-art process-based model for groundwater risk assessment and contaminant transport modeling. By improving predictive modeling of transient contaminant source terms, this research will
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are meteorology, mesoscale modelling, analysis and interpretation of meteorological datasets. We are also interested in hearing from researchers with oceanographic, as well as meteorological, science background
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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work. A model is to be developed to estimate the material mass breakdown for various cell designs and cell formats. The model will be validated from teardown analysis of commercial lithium-ion battery
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learning for dementia prediction. see here: https://ai-med.de/wp-content/uploads/2025/04/PhD_Position.pdf PhD Position: Interpretable Models for Dementia Prediction Lab for Artificial Intelligence in Medical
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Aim: Develop a mathematical model for obsolescence modelling for railway signalling and telecoms Background Network Rail operates several telecom networks which provide connectivity for various
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Martin Australia invite applications for a project under this program, exploring the development of Physics Informed Neural Networks (PINNs) for efficient signal modelling in areas such as weather
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KTH Royal Institute of Technology, School of Electrical Engineering and Computer Science Project description Third-cycle subject: Computer Science This project involves generative modeling
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systems, enabling global scalability and accessibility. Using advanced computational fluid dynamics (CFD) approaches, the project is aimed at advancing modelling capabilities for the prediction of energy