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digital twins be used to provide on-line predictions as to the future expected evolution of these critical properties as the basis for safe reinforcement learning (RL) for on-line optimal control”. In
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have extensive knowledge on processes governing cross-shore transport and can use experimental data to develop predictive models. Experiences within numerical modelling of coastal processes is considered
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- specific predictive models, the lack of explainability in AI-driven decision processes, and the difficulty of capturing long-term dependencies in time-series data. In this project, you will focus
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Postdoctoral Positions in PFAS Analytics, Degradation, and Thermophysical Properties - DTU Chemistry
thermophysical properties vary across the diverse PFAS chemical space and how these properties may be predicted using computational models. These positions offer an excellent opportunity for early‑career
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, aimed at uncovering the key traits that define successful microbial biofertilizers, and to develop predictive models that can guide the rational design of next-generation BioAg products tailored
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digital twins be used to provide on-line predictions as to the future expected evolution of these critical properties as the basis for safe reinforcement learning (RL) for on-line optimal control”. In
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the freshwater budget. It is essential to comprehend the various components of sea level change in order to enhance our capacity to predict and adapt to future sea level changes. It is expected that research