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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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models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in machine learning, computer vision, and medical
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changes and established markers for Alzheimer's disease. The project may also include machine learning methods to estimate individuals' biological age. The project is based on existing data from a prominent
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The fellow will be responsible for: Building collaborations with our multidisciplinary team (medical physicists, engineers, computer scientists, nuclear medicine physicians) to develop and implement innovative
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scientists, nuclear medicine physicians) to develop and implement innovative AI algorithms applied to medical images To lead effort on enabling translational and physician-in-the-loop AI solutions for medical
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programming languages such as Python and C++, as well as experience with machine learning frameworks like TensorFlow or PyTorch Familiarity with image processing libraries and a solid grasp of deep learning
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to assess potato dormancy break, including: data collection, processing, AI model development and classification accuracy assessment. Involved in supporting an electrophysiology-based machine learning model
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passionate plant science researchers, bioinformaticians or remote sensing/data scientists with skills in image processing or phenotyping with a collegiate and self-driven attitude towards multidisciplinary
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foundation models and agentic systems and demonstrated capability to produce workable solutions from theoretical formulations Substantial publication history in top computer vision/machine learning venues
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience