11 computer-vision positions at King Abdullah University of Science and Technology

Postdoctoral Research Fellow - Computer vision, AI, machine learning (2 years)

The Computer Vision-Core Artificial Intelligence Research (Vision-CAIR ) group led by Prof. Mohamed Elhoseiny at the CS Program  of the King Abdullah University of Science and Technology (KAUST) is

Postdoctoral Research Fellow - Computer vision, computer graphics and deep learning

The VCC center at KAUST is looking for postdoctoral researchers and research scientists in Prof. Wonka's research group. The topics of research are computer vision, computer graphics, and deep

Faculty position in computational science and engineering in materials, energy, and chemical processes

We are currently seeking outstanding candidates to join our faculty team within the Physical Science and Engineering Division (PSE) to lead pioneering research in: -          computational and data

Faculty position in Air Pollution and Atmospheric Chemistry

at establishing a world-class research program in air pollution and atmospheric chemistry. Individuals with expertise in the following research domains are particularly encouraged to apply: ·       Investigating

Research Scientist - Visual Computing Center

The VCC center at KAUST is looking for research scientists in Prof. Wonka's research group. The topics of research are computer vision, computer graphics, and deep learning. A suitable candidate

RESEARCH SCIENTIST IN COMPUTATIONAL INTEGRITY OF COMPOSITES

projects in this consortium. Responsibilities : Initiate the design, development, execution, and implementation of technology research projects in the field of Structural Mechanics and Computational

RESEARCH SCIENTIST IN NON-DESTRUCTIVE TESTING

-term plans for NDT development in collaboration with KAUST TTO and partners’ business units. Lead the development of an internationally recognized experimental and computational platform on NDT and

RESEARCH SCIENTIST IN AI AND DIGITAL TWINS OF COMPOSITES STRUCTURES

into deployable technologies. Our Vision To increase confidence and enable further penetration of composites materials in the Energy sector by availing new technologies for enhancing composite performance and

Postdoc Position: Geological Carbon Storage Modeling and Uncertainty Quantification with Deep Learning

project include two aspects: (1) based on the cutting-edge technologies from deep learning, computer vision or physics-informed machine learning, develop robust surrogate forward models to predict

Postdoc in Machine Learning

research in the field of machine learning, more specifically, deep learning and representation learning architectures. Application areas of ML include, but are not limited to, computer vision, natural