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epidemiologic methods for environmental ‘omics and related software packages, including R, SAS, Python or equivalent. Previous experience analyzing large DNA methylation datasets, bioinformatics, and use
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single cell transcriptomic data. Computational and bioinformatic skills. Experience in microscopy. Generation and analysis of mouse models. Handling of human samples. Molecular biology skills including
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to the Bioinformatics, Phylogeny and Evolutionary Genomics (BPGE- https://lbbe.univ-lyon1.fr/en/bioinformatics-phylogeny-and-evolutionary… ) team at the Laboratory of Biometry and Evolutionary Biology (LBBE) and will be
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environment covering various disciplines ranging from Developmental Biology, Cell Biology, Neurobiology, Biophysics, Bioinformatics and Computational Biology. As part of this institute, the groups at the GBE
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University of California, Los Angeles | Los Angeles, California | United States | about 18 hours ago
Proficiency in pluripotent and primary cell culture Strong background in cellular immunology assays Experience in mouse handling and procedures Proficiency in bioinformatic analysis Application Requirements
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), or bioinformatics (e.g., microbial community analysis) would be an advantage. You are able to work independently, but also within an interdisciplinary project team; You are proficient in spoken and written English
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
, functional proteomics, and AI-driven bioinformatics tool development, with the overarching goal of advancing cancer treatment through data-driven translational research. Our work bridges data science and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 12 hours ago
, functional proteomics, and AI-driven bioinformatics tool development, with the overarching goal of advancing cancer treatment through data-driven translational research. Our work bridges data science and
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-based modeling (e.g., soil carbon models; geotechnical approaches), or bioinformatics (e.g., microbial community analysis) would be an advantage. You are able to work independently, but also within
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communities in health and disease. The successful candidate will work at the interface of bioinformatics, microbiome ecology, and metabolomics, contributing to both computational analyses and laboratory