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Field
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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include, but are not limited to, using the latest computational learning-driven approaches, including computational social science, foundation models and multimodal machine learning, to enhance
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Experience with machine learning, data mining and data assimilation is a plus Knowledge of git, docker, kubernetes, and/or metadata is a plus Ability to work within a team Excellent interpersonal and
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and apply methods for analyzing genomic variations, e.g. SNV, SNP, SV, CNV, methylation, and gene expression Develop tools using machine learning and AI Prepare high-impact manuscripts for publication
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Computer Engineering or a closely related field, completed by the start date of the appointment. Research experience in at least one of the following areas: ● Chip design, tape-out, and testing
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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: Artificial Intelligence / Machine Learning Knowledge Representation and NLP methods Clinical Informatics Bioinformatics Biomedical Ontology Public Health Informatics Nursing Informatics Imaging Informatics
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ensures return to editorial staff or journal for timely publication, composes and presents research at conferences; directs research personnel. Minimum Education/Experience Requirements: PhD or MD/PhD
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of statistical genetics and genomics. This position will allow for the development and implementation of innovative statistical and machine learning approaches for analysis of genetics and genomics data. We
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sciences, computer science, machine learning, and education research. Research Themes The research themes identified for the NTO postdoc include, but are not limited to, the following: Developing