Sort by
Refine Your Search
-
Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Requirements Required skills, abilities, and knowledge: Recent or soon-to-be completed PhD (within the last 0-5 years) by the start of the appointment in computer science, electrical engineering, applied
-
Argonne National Laboratory’s Accelerator Science Division is seeking a Postdoctoral Appointee to contribute to the development of a Sub- THz Collinear Structural Wakefield Accelerator
-
. Position Requirements A formal education in Physics, Materials Science, Chemistry, or a related field at the PhD level with zero to five years of employment experience. Demonstrated experience with high
-
to contribute to other large-team scientific projects in materials engineering, chemistry, and beyond at Argonne National Laboratory. Position Requirements Required skills: Recently completed PhD (within the last
-
, computational physics, computational materials science, inverse problems, signal processing, x-ray science etc. are encouraged to apply. Position Requirements PhD completed in the past 5 years or soon to be
-
, networking, and leadership. Position Requirements This level of knowledge is typically achieved through a formal education in economics, operations research, public policy, environmental science, engineering
-
contribute to open-source code repositories and documentation. Position Requirements Required skills, knowledge and qualifications: PhD in physical oceanography, coastal engineering, computational science
-
or soon-to-be-completed PhD (typically completed within the last 0-5 years) in physics, chemistry, or materials science with 0 to 2 years of experience, or the equivalent experience through practical
-
superconducting RF (SRF) technology. Since then, a transformative SRF approach using Nb₃Sn has emerged, offering performance comparable to niobium while enabling operation at higher temperatures—potentially
-
venues Position Requirements Required skills and qualifications: A PhD degree completed within the last 0-5 years (or soon to be completed) in numerical analysis, applied mathematics, computational science