Machine Learning in Survey Cosmology

Machine Learning in Survey Cosmology Postdoctoral Fellow

Organization : National Aeronautics and Space Administration (NASA)

Reference Code : 0238-NPP-MAR26-JPL-Astrophys

Application Deadline : 3 / 1 / 2026 6 : 00 : 59 PM Eastern Time Zone

About the NASA Postdoctoral Program (NPP) : The NPP offers one?to?three?year fellowships designed to advance NASAs missions in space science, Earth science, aeronautics, and astrobiology. Fellows engage in ongoing research projects at a NASA Center, NASA Headquarters, or at a NASA?affiliated research institute.

Description : Current and future cosmology missions in the big data era of astronomy can greatly benefit from advances in deep learning. The role leads efforts to apply convolutional neural networks (CNNs) such as GANs and diffusion probabilistic models to image generation, data?to?image translation, feature / domain transfer, and super?resolution. Enhanced images can increase usable sources for weak lensing, reduce systematic errors from blending and photometric redshifts, and tighten constraints on cosmological parameters.

Responsibilities :

• Lead data?science projects that apply deep learning architectures to cosmology survey data (HSC, KiDS+Viking, DES, HST, Rubin, Euclid, Roman, SPHEREx).
• Quantify gains for upcoming missions through multi?band spectro / photometric galaxy data analysis.
• Collaborate closely with Dr. Eric Huff, Dr. Shoubaneh Hemmati, and the JPL cosmology team.

Qualifications :

Eligibility :

How to Apply : All applications must be submitted in Zintellect. A complete application includes a research proposal, three letters of recommendation, and an official doctoral transcript. For instructions, visit the NASA Postdoctoral Program website (orau.org).

Contact : Questions about this opportunity? Please email npp@orau.org.

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