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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 20 hours ago
fluid dynamics (CFD) to understand how porous structures and operating conditions can impact membrane performance. Therefore, this objective of this research is develop efficient algorithms and models
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experiments for real-world deployment. Key Responsibilities: Develop algorithms for DAS signal processing, wavefield analysis, feature extraction, and interpretation across infrastructure monitoring, urban
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aircraft (Cloud Physics Lidar and the Roscoe upper troposphere/lower stratosphere lidar). Additional projects include the development of machine learning and advanced data processing algorithms, and
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cryptography is not a must. Application of a PET algorithm to solve a real-life problem: This aspect relates to using existing PET algorithms to address a real-life problem that can be of a significant
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Job Description Are you interested in combining learning and control to develop adaptive control algorithms and contribute to the green transition? In this PhD project, you will work at the
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Nordisk Foundation Quantum Computing Programme (NQCP) and collaborate with colleagues from Copenhagen University regularly, especially within the Algorithms & Applications team of NQCP, and with
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 1 month ago
developing new retrieval algorithms. Field of Science: Earth Science Advisors: Luis Millan Valle [email protected] (626) 899-8503 Applications with citizens from Designated Countries will not be
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PhD Position in Reversible Programming for Energy Efficient Cyber-Physical Systems (MSCA Doctoral...
energy lower bound of conventional computing. The network trains a cohort of doctoral candidates who will improve and popularise reversible languages, algorithms, and architectures for energy-intensive
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successful candidate will: Develop probabilistic factor models and scalable inference algorithms for structured biological (multi-view) high-dimensional data. Develop modular methods that incorporate
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understand infant cognition, develop neuroimaging methods to better detect disrupted function following neonatal brain injury, and identify new more energy efficient learning algorithms that could reduce the