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flow modelling and simulations Responsibilities and qualifications The nature of these projects suggests that you should have a strong interest in interdisciplinary research, including coupled physical
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functional theory and ab-initio molecular dynamics simulations) with artificial intelligence techniques to parameterize machine learning force fields and kinetic Monte Carlo methods to model the molten salt
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emerge. Our theoretical approach combines analytical calculations with computational simulations. The members of the group provide a balanced mixture of postdocs, PhD students, and undergraduate students
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linked data Sensors as part of Internet of Things (IoT) and integration of sensory information in simulation models as part of Digital Building Twins (DBT) during run-time Life cycle and sustainability
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engage in developing innovative methods for interpreting and explaining the inner workings of natural language processing models. The research will broadly align with the objectives of the CopeNLU research
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experience in the following fields. Cyber-physical modelling and simulation Digital Twins Autonomous Agents and Multi-Agent Systems Machine Learning and MLOps Probability & Statistics incl. Python/R Place of
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technologies in the blue bioeconomy domain, specifically microalgae production Focus explicitly on quantitative approaches for consequential modelling and uncertainty analysis Produce high-level scientific
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that dynamically alter the detrapping and recombination probabilities. The aim of this project is to overcome these limitations by developing a Monte Carlo simulation model that treats each charge carrier and its
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. Moeslund, Aalborg University, and Law Professor Thomas Gammeltoft-Hansen, University of Copenhagen. XAI-CRED aims to develop an explainable AI (XAI) model to expose details of AI models – with a special