1,663 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" positions in Germany
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Your Job: Modeling and characterization at molecular level of selected biological processes by performing classical molecular dynamics, and employing enhanced sampling methods and machine learning
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, and construction of optical systems in the laboratory Documentation and evaluation of experimental and simulation results Development and validation of machine learning algorithms (e.g., CNNs, deep
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qualifications: PhD or equivalent achievement (proof of independent research capability) in Machine Learning, Computer Science, Physics, Mathematics, or a related field Deep theoretical knowledge and extensive
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Bayesian machine learning to improve risk management for bridge portfolios. We offer a funded PhD position in an excellent research environment. The project Our infrastructure is aging, and decisions about
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Your Job: Energy systems engineering heavily relies on efficient numerical algorithms. In this HDS-LEE project, we will use machine learning (ML) along with data from previously solved problem
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processes that produce energy and raw materials. The Department of Thermodynamics of Actinides is looking for a PhD Student (f/m/d) - Machine Learning for Modelling Complex Geochemical Systems. The job
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on the ERC project Learning Matters!. Task You will implement learning mechanics in soft matter, specifically in biocompatible hydrogels. Your hydrogels will form the walls of a synthetic vein network that can
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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Your Job: We are looking for a PhD student in machine learning to work within a project linked to the “Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE)”. Your Job: Develop
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security