10 post-doc-machine-learning Postdoctoral positions at Czech Technical University in Prague
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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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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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, 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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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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-term contract from April 2026 at the earliest till June 2027 Gross salary 55,000 – 65,000 CZK/month Six weeks of vacation per year Travel funds to attend conferences Where to apply E-mail martin.jirka
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service life in nuclear reactors. Where to apply E-mail drimakat@fel.cvut.cz Requirements Research FieldEngineeringEducation LevelPhD or equivalent Skills/Qualifications The ideal candidate
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performance and durability. Where to apply E-mail drimakat@fel.cvut.cz Requirements Research FieldEngineeringEducation LevelPhD or equivalent Skills/Qualifications Applicants should hold a PhD in Physics
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the group expertise, international collaborations, and overall research quality and impact. Where to apply E-mail drimakat@fel.cvut.cz Requirements Research FieldEngineeringEducation LevelPhD or equivalent
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or FPGA circuits in the control of electric drives, on utilization of SiC or GaN semiconductors in power converter circuit. Where to apply E-mail drimakat@fel.cvut.cz Requirements Research