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on application logic rather than underlying algorithm development), and the capability of independently driving the full "Data-AI-Deployment" process; (c) the ability to evaluate the fit between AI applications
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communication skills. Proficiency in developing deep learning models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in
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randomized evaluations of AI-driven interventions in housing, education, and workforce development, and building evaluation infrastructure for AI deployments in social sector organizations. The researcher
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, developing scalable algorithms for system optimization and control, conducting policy-relevant economic analysis, programming following best practices for reproducible research, presenting findings to academic
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algorithms, and non-inferiority margin derivation methodologies. You will develop proficiency in regulatory database management, systematic data extraction from NDA submissions, and implementation of network
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Center for Devices and Radiological Health (CDRH) | Southern Md Facility, Maryland | United States | 18 days ago
on the development of optical models, image acquisition software, image processing algorithms, and deep learning algorithms using Zemax, Python, Matlab, LabVIEW, CUDA, and other programming environments. Training
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opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT. The Future Ship and System Design (FSSD) programme aims to develop
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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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30 Mar 2026 Job Information Organisation/Company Cranfield University Department HR & Development Group Research Field Engineering » Aerospace engineering Researcher Profile Recognised Researcher
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University. Key Responsibilities: Conduct research on methods and approaches to support air traffic management studies and applications. Develop, test, and evaluate analytical models, algorithms, and tools