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analysis. Methods and algorithms including visualisation and reporting tools. Geotechnical, structural and mechanical characterisation of rock from drilling signals. Calibration and interpretation on rock
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fingerprint identification (RFFI) for Wi-Fi. You will design novel RFFI algorithms and further evaluate their performance using practical testbeds such as software-defined radio platforms. You should have a PhD
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 12 hours ago
of materials Proficiency in multi-physics FE simulations, topology optimization, and working knowledge of machine learning (ML) algorithms Demonstrated exceptional problem-solving abilities, a passion for
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science, mathematics, computational physics/chemistry or equivalent. The candidate: must demonstrate expertise in algorithmics/machine learning/artificial intelligence must show motivation in the interdisciplinary
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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
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fingerprint identification (RFFI) for Wi-Fi. You will design novel RFFI algorithms and further evaluate their performance using practical testbeds such as software-defined radio platforms. You should have a PhD
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optimiser that accelerates both workflow efficiency and materials discovery. Main Tasks and responsibilities: Own the optimiser: design, implement, and tune heuristic/metaheuristic algorithms (e.g
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to contribute to cutting-edge research in robot intelligence, machine learning, and AI-driven manipulation. This position offers the opportunity to work on real-world robotic systems and develop novel algorithms
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invites 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
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work hands-on with clinical data and build robust deep learning algorithms. We welcome applications from individuals with experience in: Experience developing deep learning models for real-time image