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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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collaboration with life scientists. Your Role: Lead the integration of multiple automated subsystems, including liquid handlers, robotic arms, and imaging modules, into a functional robotic platform, with
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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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aromatic nanobelts. Your profile: We are looking for experimentally skilled candidates, ideally experienced in multiple-step organic synthesis The candidate needs to have a PhD degree in Chemistry (with a
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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