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Field
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multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities
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using radiomic imaging algorithm in Hypoxic Ischaemic Encephalopathy). The Sophie project aims to develop a Neonatal MRI Biomarker for newborns with Hypoxic Ischaemic encephalopathy that is predictive
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associate position to conduct research in machine learning (ML) for applications in High-Energy Physics (HEP). We seek highly qualified candidates with interest and experience in ML algorithms including
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for scalable qubit architectures. Qualifications · For Theorists: o PhD in quantum information, theoretical physics, computer science, or related fields. o Strong background in quantum algorithms, error
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to develop complement/augment classical CFD methods with quantum algorithms/techniques. The work lies at the intersection of multiphase flow physics, numerical modeling, and quantum computing. Who we
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computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part
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The Role Applications are invited for a Postdoctoral Research Associate in the Department of Computer Science with a particular emphasis on the design and performance analysis of resource allocation
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applications for a Post-Doctoral Associate position, in the area of Quantum Algorithms. The candidate is expected to conduct research in computer science focusing on the combinatorial aspects of quantum
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Prof. Youngseok Kim (Ohio State University) – Quantum Computation & Quantum Algorithms Prof. Pilkyung Moon (NYU Shanghai) – Graphene, Twistronics, Novel Topological Materials Website of our team https
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methodologies in brain diseases. The candidate will work on developing advanced new algorithms, testing and validation, and applications in these data modalities. The candidate will have the opportunity to work