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/margin metrics used to assess power quality against mission demand. Model generation methodology – develop a methodology for generating reduced-order or behavioural models of the DC bus system directly
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relation to health, well-being, social inclusion and environmental sustainability: implications for the definition of innovative housing models in fragile and transforming contexts. Where to apply Website
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scenarios for achieving a low-carbon society in 2050. A key ambition of the project is to support scenario-based planning and backcasting. Rather than predicting a single future, the modelling framework
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position is offered for 4 years, starting in Spring 2027 or as soon as possible thereafter. ADAPT-X investigates how AI-based weather prediction models can be used to improve the prediction and climate
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biodiversity, and interactions between environment and society. For more information on ASE please visit https://www.ntu.edu.sg/ase . The Yanyan Cheng research group is seeking a Research Associate. This
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The project aims to develop models for food policy through a
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 days ago
for the avatarization process, i.e. obtaining a 3D, animatable model from one or several images. This is a very hard problem as shape fidelity, animatability, fast computation time and low number of required input
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of the candidate's training and experience to the objectives of the work to be developed; iii) Experience in data monitoring in the context of intelligent systems 3. Work Plan: i) Develop mathematical modeling systems
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details, please view https://www.ntu.edu.sg/medicine We are looking for a Research Fellow to support the MOE Tier 2 research project "Construct Kidney Organoids with Higher-Order Tissue Architecture
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modeling of complex, multi-site datasets. In this role, you will bridge the gap between complex data infrastructure, cutting-edge machine learning, and synthetic data generation—building automated