17 machine-learning-"https:"-"https:"-"https:"-"U.S" Fellowship positions at Nature Careers in United States
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image processing, disease detection, diagnosis, and therapeutic monitoring. The program addresses critical regulatory challenges posed by AI devices that can continuously learn and adapt, including
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computational pipelines for multiplex imaging, spatial transcriptomics, single cell RNAseq, and multi-omics data integration. Lead graph-based network and machine learning analyses of tumor immune
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successes, ARL civilian employees helped develop the proximity fuze, worked to develop ENIAC (Electronic Numerical Integrator and Computer, the first operational, general purpose, electronic digital computer
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expression, cell state-specific regulatory programs, and clinical outcomes. Related projects will include: Develop and apply statistical or machine learning approaches to model the effects of common and rare
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. This project will involve applying and evaluating statistical and machine learning models for data integration and interpretation. A strong foundation in statistical modeling will be essential for applications
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identity or expression, national origin, sexual orientation, genetic information, disability, age, ancestry, military service, protected veteran status, or other characteristics protected by law. Pay
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, disability, age, ancestry, military service, protected veteran status, or other characteristics protected by law. Pay Transparency Statement The hiring range is based on market pay structures, with individual
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information, military service, or other protected status.
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(EHR), health information exchanges, and data analysis software. Experience with health IT innovation, including working with artificial intelligence, machine learning, telemedicine, or mobile health
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immunology Experience with T cell engineering (CAR-T, TCR-T) and/or immunopeptidomics is preferred (but not required). At Dana-Farber Cancer Institute, we work every day to create an innovative, caring, and