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Applicants must have a PhD in Computer Engineering, Computer Science, or Electrical and Computer Engineering, and have published their research in prestigious conferences and journals in related
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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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The Field Engineer will support the development and deployment of a laser-based system. This role requires hands-on prototyping, electronics development, and software integration for real-time sensing and control. The candidate should have strong field experience, be comfortable working in...
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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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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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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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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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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