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microstructures along the entire process chain using machine‑learning (ML) techniques and validate soft‑sensor outputs against laboratory reference measurements Perform systematic laboratory flotation experiments
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. MATLAB, C/C++, Python. Highly motivated and keen on working in an international and interdisciplinary team. Applicants with strong background in the following fields are preferred: Machine Learning Formal
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in the following areas is also a bonus: electrocatalysis, rheology, coating technology, machine learning Intrinsic motivation to show initiative, creativity, and to work independently Excellent
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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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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 generated in the scattering
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organisation. Where to apply E-mail jobportal@careerservice.kit.edu Website https://jobs.pse.kit.edu/en/jobs/169369/scientific-associate-fmd-in-computer-sc… Requirements Additional Information Website
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Freiberg, Sachsen | Germany | 28 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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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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Behavior Models (NBM), fault detection methods, and other operational analytics based on operational data from WTs. You will apply machine learning techniques and incorporate your understanding of wind
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Your Job: In this position, you will be an active member of our Simulation and Data Lab for AI and Machine Learning in Remote Sensing, which aims to strengthen interdisciplinary research and