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Field
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development, data analysis and inference, and image analysis ▪ Ability to do original and outstanding research in computational biology, and expertise in computational methods, data analysis, software and
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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
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language, images, multimodal data, science/math, code, and scientific data. PLI is also focused on AI safety, fairness, and alignment. AI Postdoctoral Research Fellows will be appointed through the Princeton
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degree in computer science, information technology, engineering, health informatics or a related field; Research expertise and strong background in one or more of the following areas: Computer programming
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reconstruction, processing, synthesis, and registration, as well as AI for treatment outcome prediction and clinical decision making. The projects will involve using multi-modality images (CT, CBCT, MRI, PET
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developing and implementing algorithms for processing, imaging or inversion of seismic data, preferably using MATLAB and/or Python. Experience or demonstrated ability in processing and analysis of surface
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training and have opportunities to participate in faculty development programmes. The fellowship is tenable for one year. On an exception basis, a two-year programme may be supported. Service Commitment One
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) The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum phenomena
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related to the upper human airway. The successful candidate will contribute to cutting-edge research projects involving computational models, medical image data processing, and developing idealized and
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in the health sciences, including fields such as healthcare informatics, movement and rehabilitation sciences, medical imaging, remote sensing, computer vision, mental health, data fusion