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in stem cells, tissue engineering, microfluidics, organ-on-a-chip, 3D bioprinting, and non-invasive imaging to mimic various microphysiological features of tissues in health and diseased states and for
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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
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, communications, science and technology. Our students are at the heart of everything that we do, and we are committed to supporting them to pursue their career and personal ambitions. Our research is engaged
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, computer science, architecture, and engineering to develop scalable, data-informed solutions in sustainable design, construction, and energy management. The Cluster aims to modernize—and ultimately revolutionize
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-picture challenges in science and technology innovation, and has aptitude for new scientific fields. Successful candidates also demonstrate excellent communication, teamwork, and scientific/technical
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, contributing to cutting-edge research at the intersection of engineering, healthcare, and smart textiles. We seek candidates from engineering backgrounds who has experiences in healthcare device design
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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perturbation technology, AI/ML model development, or advanced molecular biology Experience in single-cell omics, spatial transcriptomics, and/or high-content imaging data analysis Demonstrated record
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-The-Shelf (COTS), all-digital radar systems linked to an array of ultra-stable, ultra-low phase noise oscillators. The project is part of the UK Quantum Technology Hub in Sensing, Imaging and Timing (QuSIT