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Field
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system, including traffic prediction, optimization, and safety enhancements. Key Responsibilities: Conduct applied research in machine learning, deep learning, and reinforcement learning for optimizing
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capable, adaptable, and collaborative researcher with deep expertise in geochemistry, economic geology, or data science, and a strong interest in working across disciplines. The successful applicant will
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Requirements: PhD degree in Artificial Intelligence, Computer Science, or a related field from a prestigious institution. Good written and oral communication skills. Proficiency in developing deep learning
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should be highly proficient with a range of machine learning approaches, including unsupervised, semi-supervised, supervised, and various deep learning techniques (e.g., convolutional neural networks
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fellowship program in cytopathology. The core responsibilities include performing superficial fine needle aspirations and on-site assessment of guided deep aspirates on both pediatric and adult patients
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languages; A good record of publications in reputable peer-reviewed journals or conferences in maritime transport, logistics management, machine learning, deep learning, and optimization; Proficient in
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and synthesis of novel materials. Key Responsibilities: Develop and apply generative AI models for materials discovery, leveraging deep learning, Bayesian optimization, and active learning. Integrate
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-disciplinary AI research and learning. Incorporates advanced methodologies such as deep neural networks and language/multimodal models, leading the preparation of scientific papers and technical reports
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and/or presentation; may assist in grant writing. Stay informed about developments in the fields of stroke, medical imaging, and deep learning to maintain and enhance your professional expertise. Lab
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looking for your next challenge? Do you have a background in machine learning or fluid dynamics and an interest in applying your skills to understand the dynamics of Earth’s fluid core and space-weather