Sort by
Refine Your Search
-
simulation, TEA and LCA, and have a good knowledge of current and future resource recovery and separation technologies. The successful candidate will 1) collect data pertaining to battery recycling, battery
-
The Theory and Modeling Group at the Center for Nanoscale Materials (CNM) seeks an outstanding Assistant Scientist to lead and support frontier research at the intersection of AI/ML, data
-
for candidates interested in the intersection of complex oxide epitaxy, quantum information, and nanophotonic to contribute to high-impact science at a national user facility. Key Responsibilities Develop and
-
computational science expertise. The ALCF has an opening for a postdoctoral position in data management targeting AI applications at scale. The successful candidate will join the AL/ML group, a vibrant
-
advanced computing, optimization, and data analytics technologies. The postdoctoral researcher will work with a team of researchers on solving challenging problems using optimization, stochastic models
-
computational science expertise. The ALCF has an opening for a postdoctoral position in data management targeting AI applications at scale. This Postdoc will join the AL/ML group, a vibrant multidisciplinary team
-
simulations, design and conduct experiments, and analyze multimodal data streams in a continuous, real-time loop with minimal human intervention (https://www.nature.com/articles/s41524-024-01423-2 , https
-
simulations on the Aurora supercomputer, using AMReX (https://amrex-codes.github.io/amrex/ ) and the lattice Boltzmann method (LBM). The candidate will develop flow/geometry-aware refinement strategies that go
-
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
-
positions is to work on AI/ML with applications to cosmological modeling and surveys. Another open position is to work with Matthew R. Becker on weak gravitational lensing analysis with Rubin LSST data