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collaborative research in biomedical informatics, including the development and application of artificial intelligence (AI), machine learning (ML), and statistical methods to analyze large-scale
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, data science using EHRs, machine learning, data mining, and natural language processing are preferred. Job Description: Develop large language models and other methods and tools to effectively use
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developing clinically meaningful machine learning models, publishing research in high-impact peer-reviewed journals, collaborating with physician-scientists, and advancing translational and grant
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) mathematics, physics, or a related STEM fields. Strong programming and data analysis skills (e.g., Python, R) Solid understanding of machine learning, deep learning, and data modeling techniques Job
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non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning models of regulatory grammar. Responsibilities
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The Argonne team is seeking two highly motivated postdoctoral researchers to help shape the next generation of secure, scalable, and continuously learning AI systems for biomedical discovery. This
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and collaborative research projects, including but not limited to: • Developing and applying bioinformatics, pharmacogenomics, AI, machine learning, and deep learning methods • Analyzing and
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lead and contribute to independent and collaborative research projects, including but not limited to: • Developing and applying bioinformatics, pharmacogenomics, AI, machine learning, and deep
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discovery and synthesis. We are seeking a creative and collaborative researcher who is excited by the opportunity to help shape the future of autonomous synthesis and self-driving laboratories. This role is
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, quantitative imaging, machine learning, and AI applications in radiology. The research area includes innovative work on developing Deep Learning Based Image reconstruction in CT on Photon Counting Detector