Astrophysics Research Associate in Data Science for Machine Learning and Citizen Science

The Zooniverse team under the guidance of Professor Lucy Fortson in the School of Physics and Astronomy at The University of Minnesota has an opening for a Research Associate position focused on machine learning and data science applications in Astrophysics. We seek a post-doctoral research associate with strong experience in data science and machine learning to further develop the world’s largest platform for citizen science. Zooniverse uses the combined input from over 2.5 million volunteer classifiers to provide labeling and other tasks across hundreds of research projects in a variety of domains. Under the onslaught of ever-larger amounts of data and to take advantage of improvements in machine algorithms, the Zooniverse team has built and implemented infrastructure to enable novel approaches that optimally combine human and machine classifiers. We seek individuals who are excited by the idea of using this new infrastructure on data-intensive sub-fields of Astrophysics with the goal of most efficiently classifying “known-knowns” while at the same time enabling the serendipitous discovery of completely new classes of objects in a given astrophysical dataset. As part of their duties, the successful candidate will support NASA research teams implementing citizen science projects and support related machine learning and data science efforts. You will have 40% time to pursue your own research initiatives. Applicants must have a PhD (or expect to receive one) in Physics or Astronomy, or Computer Science before the start date of Aug 1, 2023. Contingent on satisfactory performance and availability of funding, it is anticipated that this will be a two-year appointment (with annual renewal) with possible extension to a third year.  For a full description and application instructions please see here: https://hr.myu.umn.edu/jobs/ext/352391