117 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S" positions at Nature Careers in United States
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positions in the area of Artificial Intelligence (AI) and Machine Learning (ML) in Drug Discovery. This is a unique cluster hire initiative spanning the College of Pharmacy, Life Sciences Institute (LSI), and
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Lab at Princeton University aims to recruit a postdoctoral fellow or more senior research position to work on projects related to the development of AI/machine learning approaches for chemical and
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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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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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The Instructional Learning Designer supports the design, development, and implementation of K-16 STEMM curriculum that translates authentic St. Jude research into engaging, classroom-ready learning
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, machine learning, data science, neural engineering, computational neuroscience, and physiological data science relevant to anesthesia, perioperative medicine, pain, and critical care. The appointment will
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)medical data, applications of artificial intelligence and machine learning. You contribute to high-quality teaching in bachelor and master years of several training programmes in the faculty of Medicine and
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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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has a passion for continuing to push the boundaries of our understanding. Candidates who demonstrate responsibility, initiative, and a strong drive to learn and succeed in a collaborative environment
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Postdoctoral Research Associate - Hybrid Computational-Experimental Scientist in Bacterial Drug Resp
to antibiotics and host-like conditions. • Develop and apply statistical or machine-learning methods for interpreting single-cell and genomic datasets. • Work closely with wet-lab scientists to design perturbation