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Field
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Bioinformatics and Computational Biology headed by Ivo Hofacker. Our team works on the development of algorithms and methods for problems in Computational Chemistry, Systems Chemistry, and Computational Biology
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strong overlap in the fields of topological quantum field theory, quantum condensed matter theory, and quantum computing and algorithms. Qualifications Applicants must hold a PhD in physics or a related
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methods and tools for adaptive, AI-driven embedded algorithms to support real-time analytics and decision-making in IoT, wireless communication, and remote sensing systems Collaborate with multidisciplinary
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high-dimensional, dynamic, networked system, applying techniques from machine learning, causal inference, statistics, and algorithms. No prior biomedical training is required—just strong quantitative
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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on AI-driven end-to-end autonomous driving algorithms. Key Responsibilities: The research fellow will be leading the development of AI-driven end-to-end autonomous driving algorithms. The work will
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machine learning. Essential Duties and Responsibilities: Develop and implement advanced reconstruction algorithms for correlated and low-dose imaging modalities. Maintain and extend Python-based software
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mathematical methods, algorithms, and applications are required. Simulators are a recognized method for architectural design explorations and the implementation of software development platforms. The goal
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& Quantum Algorithms Prof. Pilkyung Moon (NYU Shanghai) – Graphene, Twistronics, Novel Topological Materials Website of our team https://sites.google.com/view/sm-cheon-group-homepage/home https
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movement; (iii) generate benefits for both society and the environment by guiding possible mitigation strategies; and (iv) drive technological progress through the development of novel algorithms