Sort by
Refine Your Search
-
interdisciplinary teams within the Materials Science division at the Argonne National Laboratory and external collaborators. Position Requirements • Ph.D. (completed or soon to be completed) in Physics, Materials
-
math, HPC, signal processing, computational physics and materials science. The appointee will benefit from access to world-leading experimental and computational resources at Argonne including some of
-
3 years) in computer science, materials science, chemistry, physics, mathematics or related engineering disciplines Knowledge of deep learning techniques for time-series and image data Experience with
-
Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
, large-scale computational science, and simulation of networked physical systems Familiarity with techniques for sensitivity analysis and handling high-dimensional problems Experience in power grid
-
. coastlines, including incorporation of levees, jetties, and wetlands. Ingest and process coastal datasets (bathymetry, topography, land use/cover) to support accurate wetting and drying and bottom friction
-
Lemont, Illinois. Preferred Qualifications: Solid knowledge and independent research capability in stochastic process, machine learning and data analytics with track records of publications. Job Family
-
, including synthesis of fuel materials and recycling of used MSR salts. The selected candidate will develop and optimize process chemistries to synthesize chloride and fluoride species, recover metals and
-
. Position Requirements PhD completed in the past 5 years or soon-to-be completed in physics or related field. Strong knowledge of coherent imaging, light modulation, Fourier-domain signal processing, X-ray
-
; publish and present high-impact research results Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of materials science, physics, electrical engineering, or a
-
, which specialize for a restricted set of floating point operations only. Many scientific applications, particularly those that are physics-driven and mission-critical, still struggle to adapt to this new