Scientific Programmer

Website Laboratory for Atmospheric and Space Physics at CU Boulder

Position Summary
This individual will join a team of scientists and engineers to support processing, calibration, characterization, and presentation of science data from NASA space science missions. Duties will entail data analysis, algorithm development, and software development using a variety of tools and techniques.

Job Duties
• Develop algorithms and implement software for processing, management, analysis, dissemination and visualization of scientific and engineering data for space science instruments
• Apply data analysis techniques and numerical methods to characterize data sets and derive new processing and calibration algorithms and data sets
• Support scientists in installing and using software tools and with presentation of data sets

Required Qualifications
• 5 years of work experience, preferably 8 years.
• Bachelor’s degree or higher in computer science, a physical science or related field or equivalent professional experience.
• Experience in the design and development of algorithms and software for processing, analysis, and visualization of scientific data sets
• Strong interest and aptitude in mathematics, numerical analysis, astronomical algorithms, and/or spacecraft orbit/attitude algorithms
• Experience programming in Python, Java, and the willingness and ability to learn new languages as necessary.
• Familiarity with modern software engineering best practices and associated tools

Due to U.S. Export Control Restrictions, only U.S. Citizens and Permanent Residents may apply.

Desired Qualifications (any of these)
• Experience processing and analyzing data from space-based scientific instruments.
• Experience using software engineering tools, such as Git, Subversion, Jenkins, and Atlassian  JIRA
• Experience with instrument calibration, image processing, and associated algorithms, such as geolocation and orthorectification.
• Experience programming in the Interactive Data Language (IDL)
• Experience with machine learning techniques

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