Sort by
Refine Your Search
-
Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Knowledge in modeling and algorithms for large-scale ordinary differential equations (ODEs) and differential-algebraic equations (DAEs) Proficiency in a scientific programming language (e.g., C, C++, Fortran
-
within the last 0-5 years) in computational science, mathematics, physics, or a related field with a focus on image processing. Proven experience in algorithm and software development. Expertise in Python
-
encompass: Catalysts Synthesis: Utilize your expertise in materials synthesis to develop novel catalysts guided by machine learning algorithms Catalyst Performance Evaluation: Utilize aqueous electrochemical
-
inverter-based resources for performing real-time simulations in Opal-RT. Develop and prototype advanced control algorithms for grid forming and grid following inverters. Develop and demonstrate
-
algorithms to develop cybersecurity, optimization, and control solutions for real-world grid applications. Candidates will be required to work in at least 4 of the following areas: Build, simulate, and
-
position to develop and apply advanced analysis methods, including artificial intelligence and machine learning algorithms and approaches, for x-ray science and instruments. These methods will accelerate
-
The Center for Nanoscale Materials (CNM) at Argonne National Laboratory is seeking an exceptional Postdoctoral Researcher to join the Electron & X-ray Microscopy Group in a core position within the Quantum Theme, focusing on Next-Generation Quantum Systems. The successful candidate will lead...
-
. These instruments and techniques support APS user programs and beamline scientists working in materials science, geology, and biology. The brain is among the most complex structures known, containing over 89 billion
-
of Light Source data such as that from the Advanced Photon Source, Biology, Astronomy, and other science disciplines. This Postdoc will have a rare chance to work on exascale supercomputing systems and novel