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Your Job: At the Institute for Advanced Simulation – Data Analytics and Machine Learning (IAS-8) we are looking for a PhD student in machine learning to work within a project linked to the
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simulation and network-based methods for epidemiological modeling. ● Develop reinforcement learning models for decision-making during epidemic outbreaks. ● Documenting the entire process and all the codes
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Simulation – Data Analytics and Machine Learning (IAS-8) at Forschungszentrum Jülich, which is dedicated to pushing the boundaries of data science theory and application. Our research spans from use-inspired
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to attach when applying: Curriculum Vitae, duly updated, dated, and signed; Copy of academic degree certificates. a) If the possession of a degree is a requirement for the grant, candidates
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. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning. Your tasks: Development and comparison of data driven models for the prediction of stresses in
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infrastructure. The research will employ a combination of semiconductor device modelling, semiconductor simulation (by imec), electrical/optical characterisation, and system-level simulation of link performance
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geometries. Current simulation-based approaches require complex 3D meshes and are often too slow for practical medical use. This project aims to create accurate and rapid surrogate models by combining physics
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the Department of Chemistry to develop innovative strategies for generating Machine Learning Interatomic Potentials (MLIPs) that accurately capture the dynamic nature of metal-ligand interactions. These models
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, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular geometries. Current simulation-based approaches require complex 3D meshes and are often too slow
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NSF-funded project on understanding tremor propagation (TP) in the human upper limb through advanced musculoskeletal modeling, muscle fatigue modeling, and simulation of tremor-suppression devices