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to alterations in mitochondrial function. During the 3-month fellowship, the fellow will use cellular models and methodologies already established in the laboratory, including cell culture, fluorescence microscopy
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experimental systems — from ecosystems to microbiology and developmental biology, from evolution to cell biology, from molecular biology to systems biology, bioinformatics, and genomics. It is always an exciting
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interdisciplinary (https://juanguanlab.wixsite.com/biophysics/ ). The team combines cell biology, quantitative imaging, and biomaterials to probe the underlying mechanisms in biophysical systems and explore new bio
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under the project “Experimentally evolving budding yeast cell size to test scaling laws in cell biology”, with the funding support from “HFSP_RGEC28/2023”. Scientific Area(s): Cell biology and Evolution
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encephalitis, and related neurological disorders. The project combines human induced pluripotent stem cell (hiPSC) technology, brain organoids, genome engineering, advanced imaging, systems immunology, and high
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information visit https://truttmann.lab.medicine.umich.edu/. Our group values curiosity, teamwork, community, and the desire for intellectual growth. We are looking for an individual interested in contributing
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Engineering at Harvard University seeks outstanding postdoctoral applicants with expertise in immunology and computational biology, specifically bulk/single cell sequencing and AI/ML workflows, to join an
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analyses of single-cell and spatial omics to advance precision medicine. Dr Chen’s research team develops AI algorithms for spatial and single-cell omics, integrates publicly available datasets into a
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advanced 3D in vitro models for studies of oral biology, disease mechanisms, tissue regeneration and biomaterial–cell interactions. The project will involve the development, characterization and application
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foundational methods for integrating single-cell and clinical transcriptomes; and train, fine-tune, and validate deep learning models using multi-omics and imaging data to predict clinical outcomes such as