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tools such as R or Python. Ability to design, execute, and troubleshoot complex experiments independently. Ability to organize and prioritize work across concurrent experiments and coordinate with a multi
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. Ability to work independently, take initiative and solve complex problems across the experimental-computational interface. Willingness to work in a highly multidisciplinary environment. Competencies and
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thereafter. Explaining complex AI models is a key challenge for ethically responsible AI. Explainable AI (XAI) research aims to provide relevant information to assist developers and users in analyzing AI
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efficiency; cycle behaviour and degradation; influence of electrode architecture and coating morphology. A particular objective will be to identify the appropriate level of model complexity required
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, electron beam lithography, diverse plasma etching tools, wafer-level bonding equipment and others. The position builds on the pioneering work in the foundry production of complex photonic integrated circuits
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. Subject description Automatic Control comprises the analysis and synthesis of models and model-based algorithms for control, estimation, and monitoring of complex dynamic systems. Project description
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, developers, healthcare professionals and other stakeholders; communicate complex legal and ethical concepts in a clear, accessible and practical manner to multidisciplinary audiences; analyse the legal and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 8 days ago
experience with a modern deep-learning framework such as PyTorch or TensorFlow. Experience developing, training, and evaluating machine-learning models using complex biomedical, imaging, or other high
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 10 hours ago
experience with a modern deep-learning framework such as PyTorch or TensorFlow. Experience developing, training, and evaluating machine-learning models using complex biomedical, imaging, or other high
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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