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of Engineering The new International Centre for Neuromorphic Systems, at The University of Manchester is hiring a Research Associate/Fellow for a two-year full-time role in Neuromorphic Systems (Algorithms). Ideal
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The new International Centre for Neuromorphic Systems, at The University of Manchester is hiring a Research Associate/Fellow for a two-year full-time role in Neuromorphic Systems (Algorithms). Ideal
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Algorithms of Pursuit søk stillingen se annonse This is NTNU NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is located in three
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. Developing and applying state‑of‑the‑art artificial intelligence and machine learning (AI/ML) algorithms to discover robust prognostic and predictive biomarkers, and design clinically actionable treatment
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learning based optimization algorithms, human and AI coordination in best decision making for urban transportation related problems. The role will focus on developing generic frameworks and innovative
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accelerator design, verification, and physical implementation using open-source tools. Explore architecture-algorithm co-design for machine learning and AI acceleration. Perform performance, power, and area
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models, focusing on industrial image analysis Develop advanced deep learning methods for power battery inspection models Design and implement novel algorithms for AI-based CT imaging Lead experimentation
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industry and international partners. For more details, please view https://www.ntu.edu.sg/atmri . We are looking for a Research Fellow to conduct research on air traffic management (ATM) algorithms and data
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theoretical analysis, including stability estimates and convergence proofs, to guarantee the reliability of the developed algorithms. Design and execute high-fidelity numerical simulations for PDE-based models
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Center for Devices and Radiological Health (CDRH) | Southern Md Facility, Maryland | United States | 14 days ago
the unique nature of clinical medical data with low disease prevalence and difficulty obtaining ground truth data. Major regulatory science gaps include lack of methods for AI algorithm training with limited