338 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" research jobs at Nature Careers
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Article) PMID: 23811687 Nature Cell Biology 13: 310-316 (2011) (Cover Article) PMID: 21336310 Molecular Cell 37: 668-678 (2010) (Cover Article) PMID: 20227371 Lab website: https://www.med.upenn.edu/apps
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the NEPHRON project, please refer to the webpage https://cordis.europa.eu/project/id/101171952 . What we offer At Maastricht University, you’ll work in an international, open, and engaged environment
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environments will provide the successful candidate with opportunities to learn from a large network of talented professionals. Prof. Mariam Jamal-Hanjani is Principal Investigator of the TRACERx study at UCL
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University of Connecticut Health Department of Regenerative Medicine and Skeletal Development 263 Farmington Avenue Farmington, CT 06030-3705 Tel: 860-679-2062 email: reichenberger@uchc.edu visit us at: https
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academiaOpportunities to work on innovative projects and network globally More information is available at: https://marie-sklodowska-curie-actions.ec.europa.eu/calls/msca-postdoctoral-fellowships-2026 Your role Your
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Medicine (https://www.irem.uzh.ch/en.html) combines cutting-edge stem cell and bioengineering research to advance regenerative therapies. Based on bio-inspired principles and novel biomimetic technologies
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Research Centre (CRC) 1450 “inSight – Multiscale imaging of organ-specific inflammation” (https://www.uni-muenster.de/CRC-inSight) The project is based in the research group of Prof. Dr. Kerstin Steinbrink
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AI in the context of the Human Cell Atlas and the European Lab for Learning & Intelligent Systems. Wet-lab: Tissue immunology, immunotherapy, cell engineering, and/or synthetic biology (Bock Lab ). We
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of Dr. Andrew Lane (https://lanelab.dana-farber.org/), within the Hematologic Neoplasia Division of the Department of Medical Oncology at Dana-Farber Cancer Institute. Located in Boston and the
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in Spatial Omics and Multi-Modal Data Integration Duties & Responsibilities: Develop computational and machine learning methods for spatial omics data (spatial transcriptomics, spatial proteomics