Sort by
Refine Your Search
-
, 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
-
, 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
-
/ Theoretical Particle Physics Nuclear Physics / Lattice QCD Lattice Field Theory Machine Learning / Machine Learning Lattice QCD and Heavy Ion Physics (more...) lattice gauge theory Appl Deadline: 2025/09/30
-
, 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
-
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
-
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
-
mathematics. These positions offer excellent interdisciplinary training possibilities in scientific computing, stochastic modeling, perturbation theory, statistics, and machine learning (applied to image and
-
, 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