1 month ago Be among the first 25 applicants Organization National Aeronautics and Space Administration (NASA) Organization National Aeronautics and Space Administration (NASA) Reference Code 0238-NPP-NOV25-JPL-Astrophys How To Apply All applications must be submitted in Zintellect Please visit the NASA Postdoctoral Program website for application instructions and requirements: How to Apply | NASA Postdoctoral Program (orau.org) A complete application to the NASA Postdoctoral Program includes: Research proposal Three letters of recommendation Official doctoral transcript documents Application Deadline 11/1/2025 6:00:59 PM Eastern Time Zone Description About the NASA Postdoctoral Program The NASA Postdoctoral Program (NPP) offers unique research opportunities to highly-talented scientists to engage in ongoing NASA research projects at a NASA Center, NASA Headquarters, or at a NASA-affiliated research institute. These one- to three-year fellowships are competitive and are designed to advance NASA’s missions in space science, Earth science, aeronautics, space operations, exploration systems, and astrobiology. Description: Current and future cosmology missions in the big data era of astronomy can greatly benefit from advances in deep learning. Architectures based on convolutional neural networks (e.g., GANs, deep image prior, diffusion probabilistic models) are well tested for applications such as image generation, data/image to image translation, feature/domain transfer, or super resolution. These applications could notably enhance astronomical measurements from combined data sets. For instance, images boosted in depth and/or resolution can be used to increase the number of usable sources for weak lensing, reduce the systematics errors due to blending, photometric redshifts, and shape measurements, and potentially put tighter constraints on the cosmological parameters measurable through weak lensing. Data from the current ground- and space-based surveys (with e.g., HSC, KiDS+Viking, DES, HST) will be used to quantify the gain for the upcoming missions (i.e., Rubin, Euclid, Roman, and SPherex) with heavy JPL, Caltech and IPAC contributions. We are seeking a postdoctoral fellow to lead this effort. Experience with deep learning frameworks is highly desirable, and familiarity with multi-band spectro/photometric galaxy data of existing and future cosmology missions as well as a broad knowledge of weak lensing systematics is preferred. The successful candidate will be working closely with Dr. Eric Huff and Dr. Shoubaneh Hemmati and other members of the cosmology team at JPL. Field of Science: Astrophysics Advisors: Eric Huff (626) 460-9834 Applications with citizens from Designated Countries will not be accepted at this time, unless they are Legal Permanent Residents of the United States. A complete list of Designated Countries can be found at: Eligibility is currently open to: U.S. Citizens; U.S. Lawful Permanent Residents (LPR); Foreign Nationals eligible for an Exchange Visitor J-1 visa status; and, Applicants for LPR, asylees, or refugees in the U.S. at the time of application with 1) a valid EAD card and 2) I-485 or I-589 forms in pending status Questions about this opportunity? Please email Point of Contact Mikeala Eligibility Requirements Degree: Doctoral Degree. Seniority level Seniority level Internship Employment type Employment type Full-time Job function Job function Engineering and Information Technology Industries Government Administration Referrals increase your chances of interviewing at ORAU by 2x Get notified about new Machine Learning Specialist jobs in Pasadena, CA . ML Software Engineer (L4/L5) - Media Algorithms Software Engineer III, AI/ML GenAI, Google Ads Los Angeles, CA $141,000 - $202,000 2 weeks ago Machine Learning Infrastructure Engineer Diamond Bar, CA $96,309.20 - $139,648.34 1 week ago Staff Machine Learning Engineer - AI Solutions Santa Monica, CA $167,700 - $246,400 2 weeks ago Los Angeles, CA $150,000 - $250,000 19 hours ago We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI. #J-18808-Ljbffr
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