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on AI-driven end-to-end autonomous driving algorithms. Key Responsibilities: The research fellow will be leading the development of AI-driven end-to-end autonomous driving algorithms. The work will
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of Finland under the supervision of Academy Research Fellow Marcelo Hartmann and Research Fellow Luu Hoang Phuc Hau (Nanyang Technological University) . We have been developing computational algorithms and
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to migration-related diversity. The position contributes to advancing methodological innovation through the creative and reliable use of machine learning, AI, and other algorithmic techniques in qualitative
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 7 days ago
management from water and energy sensors; Development of algorithms to improve data collection pipelines from water and energy sensors; Analysis of water and energy datasets using AI techniques, including
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into: Developing and implementing Quantum Dynamics algorithms for non-adiabatic. Studying the photo-activated non-adiabatic photochemistry of prototypical chromophores. Simulating measurable signals from time
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and relative position estimation. 3- Design and implement relative localisation and coordination algorithms. 4- Integrate control and communication systems; deal with disturbances and latency. 5
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page to watch video, or click here to open video) About the position The research focus of this position will be on anomaly detection. We mainly aim to develop methods that are applicable for static and
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | about 2 months ago
the last mile of maritime container Supply Chain Management, through the analysis, development, and implementation of advanced Artificial Intelligence, optimization, and decision-support algorithms within
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challenges: Successful candidates will contribute to one or more of the following research domains: development of autonomous navigation and path planning algorithms for lunar terrain traversal and regolith
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(terrestrial and NTN). The goal of this research is to design and develop algorithms and techniques that adapt to the environment, minimizing signaling overhead associated with channel estimation and enhancing