Describe a project where you reduced and analyzed observational data (imaging or spectroscopy). Walk me through your pipeline, choices you made, and how you validated the results.
Technical
Data Reduction
Spectroscopy
Photometry
Junior astronomers are often responsible for routine but critical data reduction and analysis. This question assesses your hands-on technical skills with real observational datasets, understanding of common calibrations, and ability to ensure scientific validity before passing results upstream.
How to answer
- Start with context: telescope/instrument (e.g., CFHT, Gemini, or a university 1–2m), target type (photometry, long-slit spectroscopy, IFU), and scientific goal.
- Outline the end-to-end pipeline steps you performed (e.g., bias/dark subtraction, flat-fielding, wavelength calibration, cosmic-ray removal, sky subtraction, flux calibration, telluric correction, coaddition).
- Explain key choices and parameters (e.g., algorithm for cosmic-ray rejection, extraction aperture, sky annulus sizes, telluric standard selection) and why you chose them.
- Describe software/tools used (e.g., IRAF/PyRAF, Astropy, specutils, ccdproc, CASA, IDL, custom Python scripts) and any automation or reproducibility steps (version control, Jupyter notebooks, pipelines).
- Explain validation steps: checks on S/N, comparison to archival data or standards, checks for systematics, error propagation, and sanity plots.
- Quantify outcomes where possible (e.g., achieved S/N, wavelength solution RMS, photometric accuracy) and mention how results informed the science or next steps.
What not to say
- Giving only high-level descriptions without technical detail (e.g., ‘I reduced the data with a pipeline’ without explaining steps or choices).
- Claiming perfect data or no need for validation—real data have systematics that must be checked.
- Overstating use of tools you don’t actually know (avoid naming complex packages if unfamiliar).
- Ignoring reproducibility: failing to mention scripts, documentation, or how someone else could reproduce your reduction.
Sample answer
“At the University of Toronto I reduced a set of Gemini GNIRS spectra for a project measuring stellar radial velocities. I began with detector corrections (non-linearity and dark subtraction) and created combined flats. For wavelength calibration I used arc lamp exposures and refined the solution with night-sky lines, achieving an RMS of ~0.03 Å. Cosmic rays were removed with a tailored version of L.A.Cosmic and I extracted 1D spectra using an optimal extraction with a background annulus chosen to avoid nearby sources. Flux calibration used observations of spectrophotometric standards taken the same night; telluric features were corrected using an A0V standard and molecfit where needed. I tracked all steps in a git repo with notebooks and produced QA plots (residuals, S/N as function of wavelength). Validation included comparing radial velocities of a repeat standard star (within 0.5 km/s) and verifying that the continuum shape matched archival spectra. This gave us confidence to proceed with the abundance analysis.”
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