421 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at Nature Careers in United States
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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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methodology. Applying AI and machine learning (ML) tools (including Python, R, and possibly other languages) to test and evaluate biomedical hypotheses. Developing benchmarks and working together with staff
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hypotheses. Develop, refine, and benchmark computational pipelines using statistical modeling, machine learning, and deep learning approaches. Conduct analytical validation studies including precision
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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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The IT Technician I provides technical support to internal users of computer applications and hardware (e.g., PCs, servers, mainframes). Answers questions regarding system procedures, online
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informatics, molecular simulation, computer-aided molecular design, and chemically aware machine learning. Our mission is to enable a deeper interrogation of biology through the integration of chemistry
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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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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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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