Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
are in particular targeting development of data-driven high-performance computing techniques for unbiased discovery of generative models & theory and algorithms for network inference with special reference
-
The Statistics (STAT) program in the Computer, Electrical, and Mathematical Sciences and Engineering Division (https://cemse.kaust.edu.sa) at King Abdullah University of Science and Technology
-
We invite applications for a faculty position in computational science and engineering with a focus on geophysics or fluid dynamics, as well as machine learning with one of the following experiences
-
/Online. A project at the Composites Lab is characterized by the amalgamation of experimental and computational/modeling mechanics and encompasses people with very different backgrounds to ensure we capture
-
themes: (a) learning efficiency, computational creativity (zero, few-shot, and long-tail learning of 2D and 3D vision tasks. This also includes efficient generative models that are capable of generating
-
The Bioscience Program in the Biological and Environmental Science and Engineering (BESE) Division at King Abdullah University of Science and Technology (KAUST) is launching a significant initiative
-
industry partners. Design, implement, and validate advanced reinforcement learning models. Utilize reinforcement learning and evolutionary algorithms to discover new chemical materials. Publish and present
-
framework to study marine diversity and function. Besides establishing a world-class research program, the successful candidate is expected to start a strong teaching program in Marine Systems Modeling and to
-
containment. The prohibitively high computational cost of such simulations necessitates the development of efficient and robust surrogate models for general GCS modeling tasks, especially when inverse modeling
-
is to develop a modeling framework including the use of Random-Walk method to predict NMR measurements, pore-scale finite-element modeling on 3D digital models, generated from CT-images to predict