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, the position of an Experienced Researcher with 12,50% of the regular working time is to be filled as soon as possible, for the project Non-Gaussian self-similar processes : Enhancing mathematical tools and
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, the position of an Experienced Researcher with 12,50% of the regular working time is to be filled as soon as possible, for the project Non-Gaussian self-similar processes : Enhancing mathematical tools and
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/scholarship agreement: 1 year with the possibility of extension Project leader: Przemysław Spurek Project title: Effective rendering of 3D objects using Gaussian Splatting in an Augmented Reality environment
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will bridge advanced computational mechanics with physical reality, moving beyond trial-and-error by leveraging surrogate modeling (e.g., Kriging or Gaussian Processes) to efficiently explore complex
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of expensive evaluations required for prediction and optimization. A classical approach is co-Kriging (Kennedy--O'Hagan), which models the high-fidelity response through an autoregressive Gaussian process (GP
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Environment This studentship is based at the Centre for Vision, Speech and Signal Processing (CVSSP). CVSSP is: The largest UK research centre in its field Ranked 1st in the UK for Computer Vision research
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 3 months ago
. Picchini. Fast, accurate and lightweight sequential simulation-based inference using Gaussian locally linear mappings. Transactions on Machine Learning Research, 2024 Kugler, F. Forbes, and S. Douté. Fast
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the ChirExCo project which aims to develop a multiscale modelling procedure to understand the origin of the chirality induction from chiral surface (e.g., helical silica) to achiral adsorbed molecules
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Physics, or a related discipline. Experience with recognized computational chemistry software (e.g., Gaussian, Dalton, TurboMole) is highly desirable. Experience in Time-Dependent Density Functional Theory
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composite materials (lamina properties, laminate stacking, orientation effects) is a plus. Familiarity with optimisation and/or surrogate modelling (regression, Gaussian processes, neural nets, etc.) is an