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uncertainty from climate projections into land-use forecasts. Advance Bayesian and ensemble learning approaches for non-stationary temporal processes. Implement probabilistic diffusion or generative models
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has a strong background in control engineering, with documented expertise in optimal control, adaptive control and online optimization, stochastic systems, Bayesian inference, and state estimation and
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MOFs and their hybrid materials. The primary objective is to explore the fundamental structure–property relationships that govern MOF vitrification and liquid-phase behavior, and to develop new MOF-based
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-invasive battery lifetime prediction through acoustic emission detection. This involves modeling the battery as a 3D acoustic landscape and tracking its changes over time. The expected outcomes
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tasks You will join the Grand Solution project 'DRONES: Drone-Obtained Electromagnetic Signatures' to exploore innovative approaches such as drone-based radio testing for large objects and EM signiture
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at Aalborg University’s research portal . Job description: The candidate should have a proven track-record for working with both pain and biomechanics. Additionally, the candidate should have
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recognised track records. CNAP participates in numerous international initiatives and maintains an extensive global network, making it an ideal environment to build your own collaborative connections. CNAP is