10 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" Postdoctoral positions at Czech Technical University in Prague in Czech
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(iii) complex architectures with tightly coupled components hinder modular adaptation. To address these limitations, we research a physics-guided machine learning framework that integrates physical
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, dimensionality reduction and/or machine learning methods (e.g., Lasso, ridge regression) is highly desirable. Familiarity with neurostimulation, Parkinson’s disease, or neuropsychological assessment tools is
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that preserves object identity or style. They should have a solid publication record in top-tier computer vision conferences such as CVPR, ICCV, or ECCV, and demonstrate proficiency in deep learning frameworks
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until the end of April 2026. For more information, please contact Dr. Martin Jirka (martin.jirka@fjfi.cvut.cz ). Website for additional job details https://www.cvut.cz/en Work Location(s) Number of offers
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animals and humans, contacts with the environment are not avoided and sometimes even actively sought. We will deploy this inspiration from biology to design truly robust machines with distributed control
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inertia has decreased. However, the industry has to learn how to operate synchronous generators in a system with a larger share of solar and wind that does not utilize SGs with large inertia. The candidate
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Engineering, Department of Control Engineering, daghbnab@fel.cvut.cz , https://nano.cvut.cz/researchers/nabil-daghbouj https://nano.cvut.cz/publications?name=N.%20Daghbouj https://orcid.org/0000-0002-3932-7604
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recommendation letters etc. The job start date is negotiable. Additional comments Mentor: Jan Bauer, Faculty of Electrical Engineering, Department of Electric Drives and Traction ORCID: 0000-0002-0657-1213 https
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comments Mentor: Jan Mikeš, Faculty of Electrical Engineering, Mikes.jan@fel.cvut.cz , https://leee.fel.cvut.cz/AboutUs.html#content5-v https://leee.fel.cvut.cz/Projects.html#content8-17 ORCID 0000-0003-2219
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Engineering, Physics, rezekboh@fel.cvut.cz https://scholar.google.cz/citations?user=mb1IXcUAAAAJ 10.1088/2515-7655/add59f 10.1039/D3NA00205E 10.1016/j.solmat.2022.111984 ORCID 0000-0002-0378-4598 H-index (WOS