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Science operates a Machine Shop to support the research needs of the faculty, staff, researchers, and students of the school. The Machinist will produce complex research prototype machined parts and components by
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repair computing hardware and software. Troubleshoot desktop/laptop computer security issues. Provide support for all standard productivity software (Microsoft Office - Access, Word, Excel, PowerPoint
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Science operates a Machine Shop to support the research needs of the faculty, staff, researchers, and students of the school. The Machinist will produce complex research prototype machined parts and components by
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for acquiring nanoscale volumetric images of brain tissue. This will include projects on robotic collection of ultrathin serial sections and automated high-throughput imaging. The scientist will manage
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at Princeton University. The Mesa Lab has pioneered innovative intravital multiphoton imaging techniques, paired with advanced mouse genetic tools, to observe and manipulate immune cell behavior at the single
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visitors. The person in this role will need to demonstrate a high degree of professionalism and represent a positive image of the Center for Statistics and Machine Learning and its services at all times
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biological data sets (genomics, proteomics, imaging, neuroscience), bioinformatics, molecular dynamics simulations, and related areas at the interface of computer/data science and the life sciences. Applicants
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data sets (genomics, proteomics, imaging, neuroscience), bioinformatics, molecular dynamics simulations, and related areas at the interface of computer/data science and the life sciences. Applicants must
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engineering, or in a relevant engineering field, with an extensive background and training in the operation of a wide range of spectroscopic and imaging techniques for materials characterization. Use of HRTEM
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development, service delivery with an overarching objective connecting science with society. This encompasses the development of infrastructure and processes for data standardization, data warehousing, quality