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in terms of localisation and navigation accuracy, but also with respect to computational efficiency, scalability, communication requirements, robustness, and real-time feasibility. Algorithms will
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. · Developing and implementing computationally intensive algorithms using high-performance computing (HPC) clusters. · Managing and analyzing multiple large-scale datasets, including UK Biobank (UKBB
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companies. The research will integrate techniques of numerical analysis and structure-preserving algorithms to generative modeling in AI. It will build upon the work done at IMF and SINTEF in this field. We
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Ref. 4364_All. 3 - Methods and Tools for Secure and Autonomous Brain-Inspired Cyber-Physical Systems
. The neuromorphic component will address the design, optimization and deployment of Spiking Neural Networks (SNNs) and event-based algorithms on embedded processors and specialized accelerators, including data from
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wide-field surveys (ZTF, LSST, Argus). • Develop algorithms for low-latency multi-messenger searches combining gravitational-wave, gamma-ray-burst, fast-radio-burst, and optical detections. • Make
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algorithms (e.g., NPE) for strong gravitational lensing parameter estimation. Implement domain adaptation techniques to improve model robustness and transferability between simulated and real survey data
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: Conduct high-quality research in the field of AI, focusing on multi-omics data analysis and fusion for precision medicine Design and implement innovative AI algorithms and models to solve complex problems
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. Candidates in quantum science and technology are encouraged to apply, including quantum information theory, quantum algorithms, quantum error correction, quantum systems theory, quantum materials, topological
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Responsibilities: Conduct high-quality research in the field of AI, focusing on multi-omics data analysis and fusion for precision medicine Design and implement innovative AI algorithms and models to solve complex
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Astronomy. The institute was created to advance research in the mathematical, algorithmic, and statistical foundations of data science and their application to other disciplines. In addition to providing