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of marine geophysical survey and machine learning algorithms; Job Requirements: A Bachelor degree in geophysics or equivalent and A PhD degree in geophysics / geomechanics or equivalent from a recognized
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Geosciences division is hiring an Autonomous Material Processing Postdoctoral Fellow to help transform how critical materials are produced. In this role, you'll bring together machine learning, real-time
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reactions, or transport mechanisms. • Experience in data-driven modeling or machine learning applied to membrane materials or separation performance analysis is a strong advantage. • Candidates with strong
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reinforcing our Safer Recruitment commitment. We're very proud to be a signatory of the Armed Forces Covenant . an accredited Disability Confident Leader ; autism friendly university , committed to building
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | 4 days ago
to increase ANDA review efficiency and quality. Use and development of artificial intelligence (AI), machine learning (ML) and large language models (LLMs) to help promote business intelligence in the Agency
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should also have an interest in data science, machine learning tools or artificial intelligence as applied to biological systems related to immune therapy of cancer. The postholder should be committed
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | 4 days ago
artificial intelligence applications in drug development. You will gain experience researching advanced in silico prediction algorithms, analyzing machine learning approaches for toxicity pattern recognition
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denotational semantics, abstract machines, as well as string diagrams and graph rewriting. Some knowledge of category theory would be useful but not essential. Being able to formalise the frameworks and
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-inspired learning algorithms for efficient, robust and scalable pattern recognition; (b) assist in general management of the project; and (c) perform any other duties as assigned by the project leader
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resilience of bridges under climate change-induced hazards such as flooding, scour, and debris impacts. The research aims to develop advanced numerical models and machine learning tools to predict loads