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subjects of the Computer Engineering program, including Operating Systems, Data Structures, Algorithms, Optimization, Machine Learning, Reinforcement Learning, Computer Vision, and Pattern Recognition, as
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algorithmic agents, the research explores how automation, predictive modeling, and generative intelligence transform sensemaking, decision-making, and adaptive capabilities. The goal is to develop a framework
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concepts in information processing using machine learning algorithms LanguagesROMANIANLevelExcellent Research FieldComputer scienceYears of Research ExperienceNone Additional Information Selection process
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algorithmic consequences. Topics of interest include coarse equivalents of classical graph theorems and parameters, asymptotic minors, and coarse embeddings; Where to apply E-mail job-ref-5sp0nv8qvb
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. For additional information, please visit: https://dakic.univie.ac.at/ . Your future tasks: You will actively participate in research, teaching and administration. This means: • You are involved in a well-funded
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are looking for a Research Fellow to focus
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current computing practice and be able to teach a range of computing subjects, including Cyber Security, Programming, Algorithms, Computer Logic and Architecture, Software Engineering, Database Design, both
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National University of Science and Technology POLITEHNICA Bucharest, Pitesti Branch | Romania | about 1 month ago
the response of electrochemical systems in variable operating regimes. The position involves contributions to the evaluation of constructive solutions and relevant algorithms for the control and optimization
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provisioning, and cost monitoring. Establishes testing frameworks and code-quality practices for shared research software with rigorous validation of psychometric algorithms and adaptive-testing logic
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cutting-edge analytical approaches (Multilevel Vector Autoregressive Models, Dynamic Structural Equation Modelling, Hidden Markov Models, Causal discovery algorithms, Reinforcement Learning), Contributing