Share in the thrill of space exploration and join our team! The Space Telescope Science Institute (STScI) has openings for Science Support Analysts in our Instruments Division. This is a phenomenal opportunity for early career candidates to launch a stable long-term career in astronomy. We have openings at entry-level and welcome you to apply if you have at least a Bachelor’s degree in relevant fields.
Call for applications opened on December 2, 2021 and will remain open for several months.
As a Science Support Analyst, you will typically work on an instrument team to support the development and operations of one of our flagship missions: the Hubble Space Telescope (HST), the James Webb Space Telescope (JWST), and the Roman Space Telescope. You will be responsible for reducing and analyzing calibration data for astronomical instruments (e.g. cameras, spectrographs, coronagraphs) to optimize the scientific output of our space telescopes. You will provide user support to our worldwide community of researchers on various aspects of observation planning and data analysis. You can also get involved in ground breaking astronomical research by supporting projects led by our science staff.
Who are we looking for?
- You are dedicated, hardworking, and eager to learn, and can work with minimum supervision. You seek additional training so you can grow professionally. You want to contribute to state of the art astronomy in a work environment that respects and relies upon the diversity of its staff.
- You have a Bachelor’s degree (or above) in astronomy, physics, astrophysics, planetary science, mathematics, computer science, aerospace engineering, or related fields.
- You have some experience in one or more of the following areas: astronomical data calibration and reduction (e.g., imaging, spectra, catalogs), scientific instrumentation, optics, astronomical observatory operations, astronomical research, statistical analysis, scientific programming (especially in python), software engineering, and development of astronomical software packages. Expertise in Machine Learning methodologies applied to scientific use cases and/or utilizing AWS services to optimize computational needs are desired skills, but not required.