360 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" research jobs at Nature Careers
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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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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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Solid programming skills, e.g., Python, machine learning frameworks, data analysis tools Experience with social media research or large language models is an advantage Strong analytical thinking and
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, and machine learning. The environment at GBI will allow researchers to undertake ambitious, long-term, collaborative research, and we will actively support the translation of research to commercial
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Research Assistant in Physical Computing and Wearables at the Department of Computer Science, Aar...
research is at the cutting edge of Human-Computer Interaction (HCI), personal fabrication, and physical user interfaces. As a research assistant, you will support our research team on implementing a novel
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The Section of Bioinformatics, DTU Health Tech is world leading within Immunoinformatics and Machine-Learning. Currently, we, together with a leading external pharma company party, are seeking a
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of this programme. The profile PhD in computer vision, computational biology, physics or a related discipline Demonstrated expertise in image analysis and working with large-scale imaging datasets Strong expertise in
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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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from different fields: AI (machine learning, big database, etc) Semiconductors
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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