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on the development of the SPHEREx Legacy Galaxy Clusters Catalog. The successful candidate will lead analyses to characterize galaxy populations in clusters using SPHEREx data in combination with complementary wide
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, surrogate modeling, clustering, anomaly detection, or probabilistic modeling. Proficiency in Python/Julia/R and scientific computing/data analysis tools and related libraries. Experience working with large
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emphasize multi-wavelength survey science, the galaxy-halo connection, cluster cosmology, and large-scale cosmological simulations. Analysis efforts cover topics such as CMB power spectra, CMB lensing, galaxy
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(HPC): Experience with parallel computing (MPI, OpenMP, CUDA/HIP) or running workflows on supercomputing clusters. Software Engineering: Knowledge of version control (Git), containerization (Docker
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optical interactions with atoms and molecules in gases, clusters, and liquids, providing a scientific foundation for Department of Energy–relevant applications. This appointment will emphasize theoretical
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High-Energy Physics (HEP). We seek highly qualified candidates with interest and experience in ML algorithms including unsupervised techniques, time-series modeling, and clustering algorithms