Staff Scientist California Institute of Technology - 4.1 Pasadena, CA Job Details Temporary | Full-time 1 day ago Qualifications Computational research Bayesian inference High-performance computing clusters Doctor of Philosophy Statistical modeling Spectroscopic analysis Linux Spectroscopic techniques

Full Job Description Staff Scientist Caltech Job Category:

Fulltime Temporary Exempt Overtime Eligible:

Exempt Benefits Eligible:

Benefit Based Caltech is a world-renowned science and engineering institute that marshals some of the world's brightest minds and most innovative tools to address fundamental scientific questions. We thrive on finding and cultivating talented people who are passionate about what they do. Join us and be a part of the diverse Caltech community. Job Summary This position entails modeling of the atmosphere of Uranus, using Hubble Space Telescope (HST) images as input into radiative transfer models. The ultimate objective is to calculate an improved estimate of the Bond albedo of Uranus, with well characterized statistical assessments of the uncertainties of the estimate(s). Essential Job Duties Gather key data from the HST archive and calibrate/process the images such that the quantitative analysis of the atmosphere may proceed. Utilize existing optical/ultraviolet radiative transfer codes to produce artificial Uranian atmospheres whose properties can be compared to HST image data. From these first two duties, constrain the properties of the atmosphere such that the Bond albedo may be estimated, with quantitative estimates of the uncertainties. Write up the results of these studies for the larger HST-funded science team and prepare texts and figures for scientific talks and peer-reviewed publications. Other duties as assigned. Basic Qualifications PhD in Planetary Science or Astronomy, with familiarity with Hubble Space Telescope image data. Working knowledge of the radiative transfer modeling of planetary atmospheres, both in broad wavelength coverage imaging and spectroscopy of the atmosphere(s). Expertise with methods of Bayesian inference as relevant to the assigned atmospheric modeling. Expertise with computational implementations of atmospheric radiative transfer, on Linux-based workstations and large High Performance Computing Clusters. Preferred Qualifications Experience in Machine Learning analysis of complex image data sets. Experience with spaceborne and ground-based astronomical imaging data sets and approaches. Required Documents Resume Cover Letter To be considered for this position please visit our web site and apply on line at the following link: https://hr.caltech.edu/work/job_openings We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law. je-7ee7e6f62c4b4f22884a73feb51f24fa