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under the guidance of Prof. Ivan Nourdin. Your role Conduct research in machine learning, deep learning, and probabilistic modeling, with a focus on real-world applications Disseminate research findings
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, preferably with applications to AI systems ● Design, analysis, and modeling of AI hardware such as deep neural network accelerators or neuromorphic computing ● Emerging AI/ML models and hardware
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Qualifications: Experience with aging populations or neurodegenerative diseases Familiarity with deep learning and advanced statistical approaches to neuroimaging data Prior publications in relevant areas Required
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deep exploration of cancer precursors (precancers) to identify their molecular vulnerabilities and developing methods to intercept them. The alliance is led by Professor Sarah Blagden. You will be
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the aim of conducting deep exploration of cancer precursors (precancers) to identify their molecular vulnerabilities and developing methods to intercept them. The alliance is directed by Professor Sarah
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learning in imaging analysis, clinical trials, epidemiology, genetic study, big data analysis, R language or related statistic software, or/and Python software, or programming skills of deep learning tools
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implementation of deep learning and computer vision frameworks across a range of research projects. This includes developing and training deep learning models for tasks such as scene understanding, object
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., deep learning and statistical modeling). You have knowledge of molecular genetics and genomics. You have a very good command of English (both spoken and written). You have the proven ability to conduct
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, preferably with applications to AI systems ● Design, analysis, and modeling of AI hardware such as deep neural network accelerators or neuromorphic computing ● Emerging AI/ML models and hardware
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the intersection of machine learning and genomics. The project involves the development and application of advanced machine learning and deep learning techniques to understand the sequence-function relationships