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mechanisms 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
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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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without incurring prohibitive computational costs. Unlike standard sequential sampling methods, the project will explore batch-based active learning, prioritizing diversity and informativeness in data
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(density 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
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. You will work under the supervision of Prof. Francisco C. Pereira, Assoc. Prof. Carlos Lima Azevedo (DTU), Dr. Biagio Ciuffo and Dr. Georgios Fontaras (JRC). You will work on research focused
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existing sequential and trial-and-error-based discovery approaches. The CAPeX approach will be capable of bridging the extensive separation in spatial and temporal scales between the fundamental processes
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general planning of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment of the candidate will be made by Professor Lars Jelsbak and Post Doc Carlos Neftaly