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and assessing weld quality of mechanical parts in real-time by developing machine learning models that use sensor data and other tasks that are assigned to you. Core Responsibilities: Understanding
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publications prior to the panel interview. In addition to further excelling your skills in Computer Vision/Big Data/Machine Learning analyses, this opportunity enables you to: - Work closely with clinicians
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pursue the use of machine learning techniques for data analysis. Candidates must have a Ph.D. and research experience in experimental high energy physics. The successful candidate is expected to carry out
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across a range of application areas, including education and healthcare. As these systems are increasingly deployed in high-stakes environments, there is a growing need for machine learning models
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, machine learning, governance and operations, we aim to address the complex challenges and opportunities of space exploration. CfAI is a large research group in the Department of Physics at Durham University
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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autonomous, closed-loop (“self-driving”) laboratory workflows. The role integrates catalyst synthesis, high-throughput reactor testing, and in situ/operando characterization with machine-learning and agentic
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on healthcare data. - Experience in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL) particularly in Natural Language Processing (NLP) and Computer Vision (CV) - strong record
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 20 days ago
the computational work. Researchers in the group have experience with crystal plasticity using finite element and fast Fourier transform methods, fatigue indicator parameters, process modeling and machine learning
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. in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field, with expertise in computer vision or medical image analysis. 2. Demonstrated research experience in 2D/3D