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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
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of Salary Scale W3 NBesO to be filled at the earliest possible date:University Professorship in Production Engineering and Machine Tools The Position The head of the institute represents the field in teaching
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, mathematics, engineering, natural sciences or other data science/machine learning/AI related disciplines Language requirements English C1 or equivalent Application deadline January, please see website for exact
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of molecular and biological matter using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts
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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 other multimodal datasets Design and fine-tune machine learning and deep learning models to extract meaningful patterns and predict metastatic behavior Collaborate closely with experimentalists
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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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to advancing machine learning in biomedicine. The Program focuses on developing and applying cutting-edge AI approaches to address key challenges in molecular biology, clinical research, and translational
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Freiberg, Sachsen | Germany | 25 days ago
separation models to control flotation processes. Your tasks # Develop and implement soft‑sensor concepts for continuous monitoring of ore microstructures along the entire process chain using machine‑learning
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electrification strategy, the research aims to develop a multidisciplinary framework that combines microstructure modeling, machine learning, and probabilistic simulation to link manufacturing parameters, foam