63 modelling-complexity-geocomputation Postdoctoral positions at Oak Ridge National Laboratory
Sort by
Refine Your Search
-
and functionalized sorbents for the selective extraction and recovery of gallium (Ga), germanium (Ge), and other critical minerals from complex zinc-processing feedstocks. The successful candidate will
-
theory, thermodynamics, statistical mechanics, or non-equilibrium physics Preferred Qualifications: Rich experience with transport measurements and characterization Basic knowledge of models of strongly
-
of Quantum Monte Carlo (QMCPACK, PYQMC) density functional theory (e.g. QE, VASP, PYSCF) and associated models to describe various properties of DOE-relevant quantum materials. The Materials Theory Group has a
-
Ridge National Laboratory (ORNL). Major Duties/Responsibilities: Conduct, coordinate, and report results on complex research related to following: 1) advanced electrical insulation materials; (2
-
characterization, and predictive fault tolerance in HPC systems. Architectural exploration and performance modeling of high-bandwidth memory (HBM) and DDR memory systems in the context of data-intensive scientific
-
. This position resides in the Multiscale Modeling and Materials by Design (M2MD) Group within the Materials Science and Technology Division (MSTD), Physical Sciences Directorate (PSD) at Oak Ridge National
-
the necessary chemistry and processing modifications to meet target alloy properties. Apply advanced characterization and modeling techniques and make fundamental contributions to the field. Interact with other
-
in multiscale and multifidelity simulation techniques (ab initio methods at different fidelity, machine learning tight-binding, machine learning force fields, phase-field modeling, and/or kinetic monte
-
modeling techniques and make fundamental contributions to the field. Interact with other researchers, technicians, and students to shape and drive the research agenda. Present and report research results and
-
, including parallel computing frameworks, C/C++, Julia and/or python Experience with training AI surrogate and/or inverse models Experience working in underground laboratories and/or clean rooms Excellent