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, bio-inspired amphibious robots design as well as AI application in vortical flow control and sensing. Based on physics-informed (and -informative) machine learning, we combine domain expertise (fluid
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, bio-inspired amphibious robots design as well as AI application in vortical flow control and sensing. Based on physics-informed (and -informative) machine learning, we combine domain expertise (fluid
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, advanced networks and system architecture, machine learning and cross-media perception, as well as big data and service computing. It was the first in the world to propose chaotic cryptosystems and privacy
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industrial automation, search and rescue operations, surveillance, and environmental monitoring. This postdoc project aims to address the challenges and complexities inherent in coordinating the actions
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/ Lattice QCD High Energy Physics / Theoretical Particle Physics Lattice Field Theory Machine Learning / Machine Learning Lattice QCD and Heavy Ion Physics (more...) lattice gauge theory Appl Deadline
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researchers in pursuit of advancing knowledge and making significant contributions to their respective fields. ESSENTIAL QUALIFICATIONS/EXPERIENCES PhD Graduation; Strong background in deep learning, machine
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, separation, and catalysis, with a focus on carbon capture and conversion technologies. Artificial Intelligence: Leveraging AI and machine learning to optimize material design and catalysis processes. Carbon
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Analysis, Pharmaceutics, Bioinformatics, Total Synthesis of Natural Products, Microbiology and Biotechnology, Computer-Aided Drug Design, Chemical Biology Introduce: The School of Pharmaceutical Sciences
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Recruitment Conditions: 1. Hold a doctorate degree in condensed matter physics, materials physics, or a related field. 2. Have expertise in at least one of the following areas: growth of van der
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particle physics or related areas prior to the time of employment. Preferences will be given to those with experiences in collider phenomenology, machine learning, effective field theories, positivity bounds