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the standard cosmological model. Confirming and accurately characterizing this discrepancy could point towards new physics beyond the standard cosmological framework. This thesis aims to develop and assess a new
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comparative data by fitting Ornstein–Uhlenbeck models with stepwise AIC. Methods in Ecology and Evolution. Klingenberg, C. P. (2016). Analyzing fluctuating asymmetry with geometric morphometrics: concepts
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is to develop high-fidelity models based on a test-calculation dialogue, seeking the best compromise between the degree of accuracy, the level of complexity, and the effort required to identify
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generative models, methods for approximate inference, probabilistic programming, Bayesian deep learning, causal inference, reinforcement learning, graph neural networks, and geometric deep learning. Want
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Numerical Study of Soil Remediation by Thermal Desorption with a Focus on Industrial Decarbonization
, coupling fluid flow and heat transfer phenomena with desorption kinetics. The developed model will be informed by operational data from real industrial sites and will incorporate literature data for common
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Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Paris 15, le de France | France | 13 days ago
set of parameters, the background values of the fluxes and the geometrical parameters of the internal space (like its volume or sizes of different topological cycles), called moduli. They span a “moduli
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uploaded using the dedicated electronic form. helpdesk: petra.koudelova@fsv.cvut.cz Mathematical Modelling and Numerical Simulation of Flow, Transport and Phase Transitions Description: Investigation of free
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-Reflective Sensor Oculography (PSOG), addressing calibration and cross-user generalization challenges through the use of hypernetworks. PSOG signals are highly sensitive to geometric, anatomical, and
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. Specific Requirements Knowledge: Interoperability with IFC formats. Digital Twins. Evaluation of the geometric and semantic representation of the models. Relational databases. Professional Experience: As a
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INFORMATICA - SCIENZA E INGEGNERIA | Italy | 3 months ago
Description This research project aims to develop a new artificial intelligence model for dense scene understanding from images, that is, for estimating multiple geometric and physical properties. The key