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following areas: 1) statistical genetics/genomics/omics, or 2) deep learning/AI. Most importantly, we value candidates who demonstrate both the ability and drive to rapidly learn and implement recent advances
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and sets up experiments in hybrid research environment. 2. Researches artificial intelligence/machine learning algorithms, database design, deep learning, big data, and cloud computing. 3. Publishes
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record (EHR) as well as MyChart data, with the opportunity to work on applications of machine learning/deep learning/ Natural Language Processing in novel areas of healthcare. The position is open for a
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on the development, ecology, evolution, and physiology of marine organisms worldwide from the intertidal zone to the deep sea. Position Summary The Oregon Institute of Marine Biology seeks qualified applicants for its
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moves. Success will be measured by having published or contributed to papers in top venues (e.g., Nature Science of Learning, Computers and Education, ACM Learning at Scale, Educational Data Mining) and
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statistical approaches. A fundamental understanding of Deep Neural Networks as applied to high-frequency time series datasets, including the ability to design and implement custom NN models in PyTorch, as
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materials property predictions. A deep understanding of materials properties and close connections in academia and industry enable the group to explore exciting research avenues. For more information about
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collaborative research environment which will provide the opportunity to perform cutting-edge research in deep learning and scientific computing. Deliver ORNL’s mission by aligning behaviors, priorities, and
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, operations, and culture of DOE. As a result, fellows will gain deep insight into the federal government's role in the creation and implementation of energy technology policies; apply their scientific, policy
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, computer science, bioinformatics, or other related disciplines is required. Strong interest, research background and experience in the methodology research in statistical genomics, machine/deep learning