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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 18 days ago
scientists, including experts in machine learning and Al. The School Research School of Chemistry (RSC) strives for excellence in research and training in the areas of Biological Chemistry, Materials Chemistry
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: neuromorphic algorithms, machine learning, classifier development, AI programming Key tasks include experimental and/or computational research, collaboration within the project team, publishing results in high
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. • The ability to work independently and collaboratively within a multidisciplinary team. • Strong writing, critical thinking, communication, and presentation skills. • Experience in Machine Learning is a
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to teach two courses per year: one lower-level course, such as Introduction to African American Literature, and an upper-level course such as Black Aesthetics, Early African American Print Culture, or a
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following mandatory requirements: a) A completed degree in Computer Engineering; b) Good knowledge in the areas of Machine Learning, Natural Language Models, and Computer Security – information to be provided
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exciting project that will develop new approaches to handle missing data in statistical analyses based on machine learning methods. The Research Fellow will be based in the Department of Medical Statistics
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third largest university by intake in Singapore. SIT’s mission is to innovate with industry, through an integrated applied learning and research approach, so as to contribute to the economy and society
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health records (EHR), waveforms from bedside monitors, radiology images and wearable sensors. This position offers a unique opportunity to work closely with clinicians on applications of machine learning
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or translational research experience Knowledge of machine learning, Bayesian modeling, or statistical method development Ideal Personal Attributes: Independent, proactive, and scientifically curious Detail-oriented
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, together with significant experience in computer programming and computational biological applications. A strong background in statistics and biology. Formal training and/or research experience in genomics