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invasive sensing tools to monitor metabolites, oxygen, carbon dioxide, pH, and other parameters. Ideally, the methods can function in parallel and on a large scale. The research is vital to understand key
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engineer or computer scientist to establish a robotic platform for autonomous experimentation in organoid culturing. You will work with life scientists to design, integrate, and establish the platform’s
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users: provide project consultation, training and hands-on support, schedule and prioritize measurements, and ensure timely data delivery Drive method development for single-cell MSI and integration with
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mass spectrometers and nano/UHPLC systems Experience with state-of-the-art proteomic workflows, including MS acquisition (e.g. DDA, DIA, PRM) and data analysis with dedicated software tools. Computer
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population health issues. Methods used in the group’s work include quasi-experimental techniques, descriptive epidemiology, and randomized trials. The fellow will be expected to publish in high-impact peer
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. Prerequisites Doctoral degree with quantitative training or research experience Training and experience in quasi-experimental methods is a plus Strong coding skills in R, Stata, or other statistical software