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University of California, Los Angeles | Los Angeles, California | United States | about 23 hours ago
with Microsoft Azure or similar cloud-based technologies and analytics platforms such as Databricks is preferred. Proficiency in Python or R is required, and experience using analytical documentation and
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research will involve Python scripting within the Thermo Fisher AutoScript environment to control operation of the microscope beam, stage, detectors, and spectrometers, with a particular emphasis on annular
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, from initial target geometry creation to pre-processing, data analysis, scientific visualization, and final data reduction. Developing custom post-processing scripts in Python for detailed blast wave
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biology, or a related field Experience designing, executing, analyzing, and interpreting quantitative experiments, including high-throughput screens. Experience with coding software such as Python, R, and
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physiology Competency in scientific programming (e.g. ImageJ, Python) for data analysis and image processing. About the Lab & Environment. The Krishnakumar lab is a highly collaborative group with access
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to continue during the academic year. Minimum Qualifications Preferred Qualifications • Experience using software in Java, Python, Photoshop, HTML, and CSS programming language • Ability to travel to COSMIAC
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License: No If yes, what is the preferred licensure/certification?: Preferred Computer Applications: Microsoft Outlook, Not Applicable Preferred Other Computer Applications: Python, Unix Preferred
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 6 hours ago
Laboratory experience following established scientific protocols Coding experience in both Python and Matlab Experience using LaTeX Applicant Instructions: Applicants should be prepared to upload the following
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degree in Information Systems, Computer Science or related field plus at least 1 year of relevant experience to include: Experience in Python Developing web applications using modern open-source JavaScript
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to and build upon modern Python-based statistical modeling tools such as pyhf, supporting likelihood publication, large-scale analysis combinations, and result reinterpretation across the ATLAS