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Field
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collaborative research in electromagnetic sensor systems, including theoretical analysis, numerical modeling, AI-assisted sensing algorithm development, and experimental validation Qualifications: An earned PhD
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, DMC). Development and implementation of Quantum Monte Carlo algorithms. Numerical simulation of many-body quantum systems. High-performance computing (HPC) and Linux environments. Scientific programming
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Position Details Position Information Internal Posting? Posting Number SP005436P Position Title Enterprise Developer II Division/College Information Technology Services Department Enterprise
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, implementation, and evaluation ● AI in public management, government operations, and public service delivery ● Algorithmic decision making, accountability, and transparency ● The responsible and ethical use of AI
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: Wireless Communications Group: Mobile Systems - Av Work Objectives: Energy-efficient wireless power transfer system using RIS-enabled beamforming and optimized power management algorithms to ensure
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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 The project aims to develop robust, intelligent
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applications. ● Research and development of real-time estimation algorithms and adaptation to operating conditions Where to apply Website https://www.unimore.it/it Requirements Additional Information Eligibility
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, memory usage, and scalability (as a function of network size and the size k of the subgraphs); - Research the most recent developments (post-2019/2021) in the field to identify any new algorithms
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 1 month ago
the information they contain. This project, part of the Helmholtz School for Marine Data Science (MarDATA), will develop new data science methods to improve the interpretation of biodiversity patterns from long
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of advanced Federated Learning algorithms. The research activity will be aimed at the study, implementation, and validation of distributed learning solutions. Where to apply Website https://pica.cineca.it/unina