149 machine-learning "https:" "https:" "https:" "The University of Edinburgh" uni jobs in Czech
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documents uploaded using the dedicated electronic form. helpdesk: petra.koudelova@fsv.cvut.cz Machine learning for 3D printed multifunctional metamaterials Description: The PhD topic focuses on the use
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uploaded using the dedicated electronic form. helpdesk: petra.koudelova@fsv.cvut.cz Physics-guided learning for machine control Description: Robust machine control assumes modeling of robot-environment
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announces an open competition for the position Ph.D. student - Machine learning-based tools for multiparametric enzyme optimisation Workplace: RECETOX, Faculty of Science, Masaryk University in Brno, Czech
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description The project will use bioinformatic analysis together with comparative approaches to individual cells, and machine learning to investigate how the vertebrate head evolved and what mechanisms control
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on tungsten samples and candidate tungsten alloys will validate the simulations and guide the design of more dust-resistant materials. Finally, we will use machine learning to integrate simulation and
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scanning and Time-of-Flight (ToF) sensors, to enable robust material identification directly in non-laboratory, real-world environments. The acquired data will be processed using advanced machine learning
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15 Apr 2026 Job Information Organisation/Company Czech Technical University in Prague Department Department of Electromagnetic Field Research Field Technology » Computer technology Researcher
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of normal and pathological physiology. It consists of a number of scientific and service departments and shared equipment for the research (http://www.fgu.cas.cz/en/ ). The Laboratory of Molecular Physiology
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utilization. ● e) Applying machine learning techniques: Dynamic selection of optimal post-processing protocols will be achieved by evaluating real-time network conditions and adjusting based on metrics
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theory, Machine learning and multivariate statistics, Application in neuroscience, climate research, economics, ...). COBRA is a part of the Department of Complex Systems of the Institute