2015-2016 WRF and Moore/Sloan Postdoctoral Fellow
Astronomy & Physics, Machine Learning, Reproducibility & Open Science
Jes Ford was a Moore/Sloan Data Science and WRF Innovation in Data Science Postdoctoral Fellow from 2015-2016. She is currently working at Recursion Pharmaceuticals.
Data Scientist, Backcountry.com, Park City, UT – started September 2016
Moore/Sloan Data Science and Washington Research Foundation Innovation in Data Science Postdoctoral Fellow, 2015-2016
Department of Astronomy
Mario Juric, Astronomy
Jake VanderPlas, eScience Institute
Ph.D. Candidate, Physics, University of British Columbia B.Sc., Physics, University of Nevada, Reno, 2008
My research interests are cosmology, clusters, and the evolution of large-scale structure. For my Ph.D., I am working on gravitational lensing magnification, and comparing with results using the much more common shear technique, in order to study the distribution of dark matter in the halos of galaxy clusters in CFHTLenS and COSMOS. All matter in the universe bends light, a phenomenon known as gravitational lensing, and this effect can be used to study the properties of galaxies, clusters, and the mysterious dark matter and dark energy that make up most of the universe. I am interested in improving the characterization of galaxy clusters in large astronomical surveys, and in promoting open and reproducible science by creating and contributing to open source code for gravitational lensing and galaxy cluster analyses. In the near future I am interested in advancing characterization and modeling of halo miscentering offsets in various cluster catalogs, and I am also preparing to make much of my code publicly available. I am actively studying machine learning and data science techniques, for extracting insights from large astronomical surveys and making algorithms more efficient and easier to use.