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data for model calibration and validation. Apply sensitivity analysis and optimization algorithms to refine model parameters and improve predictive accuracy. Contribute to code development, documentation
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, the next step in this project is to address sparse optimization for tensors. We propose the integration of randomized algorithms into sparse optimization frameworks for the purpose of completing
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) to predictive maintenance challenges. Develop and fine-tune LLMs to analyze and interpret unstructured data (e.g., maintenance logs, sensor data, technical reports) for predictive insights Collaborate with domain
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using simulation-based parametric studies. Couple computational results with experimental data for model calibration and validation. Apply sensitivity analysis and optimization algorithms to refine model
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such as air quality monitoring, water leak detection and energy monitoring of electric vehicle batteries. The candidate will need to master sensor technologies, embedded systems, and communication protocols
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and sustainable sensor systems for industrial applications. This position offers an exciting opportunity to contribute to cutting-edge research in the field of sustainable materials to develop promising
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: Statistical model development: Led the development of advanced statistical models and machine learning algorithms for forecasting precipitation and temperature in Morocco. This will involve data analysis, model
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terms of research and education, covering all aspects of computer science, including artificial intelligence, machine learning, data sciences, algorithms, databases, cloud computing, software engineering
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, including artificial intelligence, machine learning, data sciences, algorithms, databases, cloud computing, software engineering, networking, operating systems and security. Job Description We are seeking
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interdisciplinary team focused on developing innovative numerical algorithms and software to address emerging challenges in scientific computing and machine learning. The research will emphasize both theoretical