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Efficient and Reliable Numerical Solution of Dynamic Optimization School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Yuanbo Nie Application Deadline: Applications
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 14 hours ago
, and astrobiology. Description: We are seeking a postdoctoral researcher specializing in silicon detector characterization and optimization for high-performance space imaging applications. The
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our community. We are now looking for a Doctoral Researcher in AI and Quantum-Inspired Optimization for Sustainable Energy Systems Are you passionate about developing AI-based and quantum-inspired
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 5 hours ago
, 2026 Description This is a unified application form for all positions in the Optimization and Machine Learning Lab at KAUST led by Prof Peter Richtarik, including Research Intern MS/PhD Student PhD
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/research-teams/iwine ). YOUR TASKS PhD Position in AI-Driven Resilient RAN Optimization for 6G and O-RAN Architectures JOB DESCRIPTION This PhD research aims to investigate beyond state-of-the-art
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fully determine the torsional response using conventional methods alone. Unknown external forces and torsional response can instead be estimated using methods such as convex optimization or Kalman
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, optimization, market microstructure, simulation, forecasting, and large-scale data analysis, drawing on a broad quantitative toolkit to develop new insights and approaches As a Quantitative Researcher
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, optimization, market microstructure, simulation, forecasting, and large-scale data analysis, drawing on a broad quantitative toolkit to develop new insights and approaches. As a Quantitative Research
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• nonlinear optimization is beneficial. What we offer: • Close mentorship: the PhD student will receive responsible and careful mentorship by both principal investigators, who emphasize fostering a healthy
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processing conditions Apply data-driven and machine-learning methods for multi-objective optimization of efficiency, reproducibility, and operational stability Study intrinsic material stability