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Post-Doctoral Associate - Machine Learning Techniques - Astrophysical Problems (Kelly/Scarlata)
Research Description:A postdoctoral appointment in the application of machine learning techniques toseveral astrophysical problems at the University of Minnesota. Projects include i)analysis and interpretation of individual stars and supernovae highly magnified byforeground cluster lenses using the Hubble Space Telescope, JWST, andground-based data, ii) preparation for time-domain observations, including of TypeIa supernovae, with the Nancy Grace Roman Space Telescope, and iii)development of simulations of galaxy populations for the Nancy Grace RomanSpace Telescope Galaxy Redshift Survey.Job Duties30% Measurement of star formation histories of arcs strongly lensed by foregroundgalaxy clusters from photometry obtained using machine learn


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