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Field
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imaging and spectroscopy. Experience with data analysis or the ability to perform basic biochemical work with proteins and DNA, e.g., fluorescence labelling, enzymatic reactions will be highly rated in
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in and knowledge of the broad area of soft matter, with expertise in microscopy, optical imaging, and data analysis. Experience in building and working with optical traps, and familiarity with colloid
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candidate will have expertise in data analysis/interpretation, publication of results in the scientific literature, and a valid driver’s license. Additional Skills: Strong interpersonal skills, excellent
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-Intensive Engineering and Science (part of the new Data Science and AI center), and at the National Radio Astronomy Observatory. Required qualifications are: PhD in Astronomy, Astrophysics, Physics, or a
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Department of Chemical and Biological Engineering at Princeton University. The position is in the broad area of renewable energy systems synthesis, analysis, and optimization. The goal of the project is to
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with Dr. Kate Hoffman to define and lead specific research objectives aligned with the funded aims. Responsibilities will include project management, coordination of data collection and analysis
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modification. By marrying first-principles theory – trade-off analysis, game theory, reaction-diffusion, and consumer-resources models – with single-cell tracking and synthetic community experiments
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in cells and using an age-dependent murine disease model to analyze neuropathogenic mechanisms. ● Perform POWV experiments and data analysis following in primary cells and cell lines in BSL2/BSL3
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skills in programming, modelling, and data analysis. Experience in formulating and solving mathematical optimization problems, as well as working on real-world demonstrators, is an asset. Proficiency in
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soft matter, with expertise in microscopy, optical imaging, and data analysis. Experience in building and working with optical traps, and familiarity with colloid chemistry and surface functionalisation