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(e.g., including simulation, prediction). Enable the evolution of integrated data/models all along the Digital Twin lifecycle Ensure the consistency of integrated data and models with regard to potential
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of millions of lakes worldwide. The successful candidate will create innovative solutions that significantly enhance large-scale environmental simulations and meaningfully advance the modeling of global lake
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-layer and cloud processes in the air-mass transformations that follow moist intrusion events into the Arctic. Using large-eddy simulation models, you will set up and run case studies of observed air-mass
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Postdoc (f/m/d): Machine Learning for Materials Modeling / Completed university studies (PhD) in ...
Area of research: Scientific / postdoctoral posts Starting date: 01.07.2025 Job description: Postdoc (f/m/d): Machine Learning for Materials Modeling With cutting-edge research in the fields
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found on hpc.uni.lu . The activities include classical HPC applications such as simulation and modeling, but also artificial intelligence and machine learning, bridging computational science, with data
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evolution, and further to modelling. Investigating transcriptional profile of lncRNA. It can be expression quantification, alternative splicing, start sites properties. Performing AI modeling and developing a
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) will project how management strategies, climate change, and wildfires will shape western forests over the next century using state-of-the-art simulation models. This role offers leadership opportunities
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project “ALPS - AI-based Learning for Physical Simulation”. Expected start date and duration of employment This is a 2–year position from 1 October 2025 or as soon possible. Job description You will be
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aims to develop a novel high-performance Particle-In-Cell (PIC) code for plasma physics simulations, leveraging the capabilities of exascale computing systems. By optimising PIC algorithms for modern
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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