25 parallel-and-distributed-computing-phd research jobs at King Abdullah University of Science and Technology
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for chemical and morphological characterization. The candidate should preferentially have a PhD in chemistry, polymer science, or membrane preparation and characterization. Besides the salary (contract of 2
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genomics, protein engineering, cloning/assembly workflows, cell line development). You will work closely with computational experts to establish innovative, high-throughput, high-fidelity screening platforms
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/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
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boasts world-class equipment, research and recreational facilities, and computational resources. It is the leading university in citation per faculty according to the QS Rankings. Further information can
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equipment, research and recreational facilities, and computational resources. It is the leading university in citation per faculty according to the QS Rankings. Further information can be found
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Three postdoctoral positions at the King Abdullah University of Science and Technology (KAUST) under the mentorship of Prof. Jürgen Schmidhuber.This project, located at the intersection of Reinforcement Learning and Material Science, focuses on developing innovative solutions for the discovery...
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generous funding for research, a cutting-edge genomics facility, and top-tier high-performance computing infrastructure, fostering an excellent environment for genomics-based research. The position is fully
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computational resources. It is the leading university in citation per faculty according to the QS Rankings. Further information can be found at www.kaust.edu.sa .
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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
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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