326 machine-learning "https:" "https:" "https:" "https:" "https:" "Cardiff University" 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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in Spatial Omics and Multi-Modal Data Integration Duties & Responsibilities: Develop computational and machine learning methods for spatial omics data (spatial transcriptomics, spatial proteomics
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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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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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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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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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-species interaction in gas–liquid bioreactor platforms. Deliver scientific excellence through high-impact publications, dissemination and outreach. Teach and develop courses at BSc and MSc levels in
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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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QGG Aarhus University seeks two Postdoctoral researchers in Quantitative Genetics of sustainable ...
tools or functional genomic information or OMICS to improve genomic prediction models. The persons hired will collaborate with industry partners, teach at undergraduate and graduate levels, and supervise
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in wireless communications and networking Background in AI and machine learning is an advantage. Experience and skills Knowledge of random-access protocols (e.g. IEEE 802.11 family). Understanding