18 machine-learning-modeling-"https:"-"Computer-Vision-Center" Postgraduate positions
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GitHub. Essential Duties and Responsibilities: Assist in the development and implementation of AI agents and machine learning models for civil engineering applications Develop, test, and optimize models
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Proficiency in at least one programming language, preferably Python; experience with scientific computing, numerical modeling, or machine-learning frameworks is an asset Strong analytical skills with a solid
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the use of large language models to support neural network design and data preprocessing. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning
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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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modeling and model–data fusion techniques, and developing faster, machine-learning–based tools that can stand in for slow model simulations. These tools will be used to test how model parameters influence
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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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heavily relies on empirical determination of key model parameters. By combining protein structure descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange
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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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to be part of a unique and diverse community that works on high-impact research, educational, business, and societal problems. Position Summary The Machine Learning Researcher - Epidemiology will report
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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