14 machine learning uni jobs at King Abdullah University of Science and Technology in Saudi Arabia
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capillary pressure, and data-driven, physics-driven machine-learning. Applications are sought for a two-year postdoc position, and will work closely with an industry partner. The position will include a
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Application documents: 1) Brief cover letter, explaining your motivation for applying, 2) Detailed curriculum vitae (including your email address), 3) Complete transcript of grades from all your university-level studies. We do not ask for more information/documents at this point (but you can...
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the Climate and Livability Initiative (CLI). The successful candidate will engage in machine learning (ML) and artificial intelligence (AI) projects aimed at forecasting natural hazards, assessing climate
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Postdoctoral Researchers to work on research problems at the interface between a selection of the following areas: - Bayesian inference for deep learning - Generative modeling - Computational statistics
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Bioinformatics (generative protein design) Methodology (machine learning, deep learning, and AI) for analysis and prediction of genotypic variation Methodology (machine learning, deep learning, and AI
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biosynthesis Biomolecular design: engineering proteins, enzymes, and other biomolecules with specific properties with AI or machine learning Cell-free expression systems: utilizing isolated cell components
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analysis (e.g., paper-based droplet systems) Nanopore transport Digital/droplet, analytical and reactor microfluidics Organs on a chip for diagnostics and drug discovery Methodology (machine learning, deep
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in the area of Computer Science and Engineering. Particular areas of interest are machine learning, artificial intelligence, computer architecture, embedded systems, and their applications. Applicants
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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
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. Embedded systems, fault-tolerant computing, hardware-friendly machine learning, low-power computing to enhance safety, efficiency and accessibility, in-vehicle computing, medical and wearable devices, modern