Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Argonne
- CNRS
- Delft University of Technology (TU Delft)
- National Energy Technology Laboratory (NETL)
- Oak Ridge National Laboratory
- Princeton University
- Stony Brook University
- University of North Carolina at Chapel Hill
- AALTO UNIVERSITY
- Aarhus University
- Chalmers University of Technology
- Harvard University
- ICMAB
- ICN2
- KTH Royal Institute of Technology
- SUNY University at Buffalo
- University of California
- University of Lille
- University of South Carolina
- University of Southern California
- University of Sydney
- University of Texas at Dallas
- Uppsala universitet
- 13 more »
- « less
-
Field
-
National Energy Technology Laboratory (NETL) | Albany, New York | United States | about 24 hours ago
be given the opportunity to copy over what they had previously submitted. All documents must be in English or include an official English translation. If you have questions about the application
-
this position, you will employ molecular dynamics (MD) simulations to investigate the underlying atomistic mechanisms of LCI in steel grain boundaries and the inhibitory role of silicon. Your MD-based approach
-
validation, this position addresses the underlying governing atomistic mechanisms. Within this position, you will employ molecular dynamics (MD) simulations to investigate the underlying atomistic mechanisms
-
, Integrity, Teamwork, Safety, and Service Preferred Qualifications: Deep expertise in atomistic and multiscale simulation methods (e.g., MD, enhanced sampling, QM/MM) Experience improving performance and
-
and application of methods for simulating magnetism, particularly atomistic and multiscale simulations. The successful candidate will have the opportunity to collaborate with leading experimental and
-
the Peng Research Group . The successful candidate will conduct research at the intersection of scientific AI, atomistic simulation, computational catalysis, and data-driven materials discovery. The position
-
interiors. This work will rely on large-scale atomistic simulations paired with machine-learning interatomic potentials. Duties: ● The postdoc will generate density functional theory reference data, use
-
reactions, catalyst surfaces and interfaces, reaction mechanisms, activity and selectivity develop reproducible atomistic simulation and high-throughput workflows using Python, ASE and relevant DFT software
-
generation, targeted atomistic simulations, structural descriptor extraction, and predictive models. The work will aim to establish links between local pore geometry, structural disorder, sodium adsorption
-
Responsibilities Theory Quantum transport modeling using NEGF; first-principles materials and interface calculations using DFT (VASP, Quantum ESPRESSO, or equivalent). Atomistic spin dynamics