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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are looking for a Research Assistant to
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for classifying user activity in office buildings using power consumption data, with a focus on probabilistic approaches such as Gaussian Processes that provide principled uncertainty quantification
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-Informed Machine Learning perspective [1]. The doctoral student’s thesis will focus on operationalising this perspective through the development of Biology-Informed Gaussian Processes (BioGPs
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mainly rely on Poisson log-normal (PLN) models with Gaussian latent variables, in which the observed dependencies between species are directly interpreted as ecological interactions. Although these models
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. Description: The transition in the Arctic from multi-year ice to first year ice raises the urgency of process understanding and modeling of sea ice formation/melt processes, including the interaction with
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models/flow matching, and Gaussian processes for realistic load, generation and voltage time series. You will embed physical constraints into generation: power-flow consistency (Kirchhoff's laws) as soft
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range of statistical fields, including high-dimensional data analysis, Bayesian methods, spatio-temporal modelling and non-Gaussian modelling. We also provide statistics education at all levels. More than
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method) leveraging Gaussian process (GP) emulators to isolate sensitive parameters and optimize workflow computational costs. Calibrate and validate computational models against individual and population
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Job related to staff position within a Research Infrastructure? No Offer Description Neural reconstruction pipelines (e.g. Gaussian Splatting) and 3D sensing technologies such as LiDAR and
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communication, sensing and power. The role also includes validating these methods through simulations and physical robot experiments. The development of uncertainty aware methods, such as Gaussian processes with