121 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Washington University in St" research jobs at Nature Careers in United States
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environment and encourage candidates from diverse backgrounds to apply. Responsibilities: Assist with laboratory research on multiple projects. Perform experiments as directed, report and communicate data
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discipline The ability to independently design and execute experiments and interpret data Expertise in at least one of the following areas: Super-resolution imaging, including Stimulated Emission Depletion
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of experiments. Accurately record experimental procedures and data. Prepare and report results/ data leading to posters, presentations, or publications. Provide guidance to less-experienced team members. Perform
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products. CDRH provides consumers, patients, caregivers, and providers with understandable and accessible science-based information about products. CDRH facilitates medical device innovation by advancing
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, political beliefs, national origin, age (40 or older), sex (see: Sexual Misconduct, Discrimination policy ) sexual orientation, genetic information, gender identity, gender expression, disability, or veteran
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curiosity and a desire for real-world impact. Mayo Clinic has digitized over 15 million gigapixel digital pathology slides, representing an incredible diversity of complex diseases of all types. This data is
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-derived organoids and assembloids, engineered ECM environments, and in vivo mouse models, working in close partnership with the lab's computational team to generate data-rich spatial multi-omics datasets
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-EM sample preparation, data collection, and high-resolution structure determination • Process and refine complex cryo-EM datasets using strong computational skills (RELION, cryoSPARC, etc.) • Conduct
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bioinformatics, computational biology, genomics, statistical genetics, or a related quantitative field, together with demonstrated expertise in large-scale genomic data analysis and significant experience in
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of complex diseases of all types. This data is now helping to power fundamental advancements in digital pathology, including the training of class-leading pathology foundation models and task-specific models