55 parallel-computing-numerical-methods-"DTU" Postdoctoral positions at Argonne in United States
Sort by
Refine Your Search
-
modeling is critical Considerable computational expertise in using quantum mechanical methods to calculate reaction mechanisms and kinetics in heterogeneous systems is essential Ability to program in C++ and
-
The Center for Nanoscale Materials (CNM) at Argonne National Laboratory is seeking postdoctoral researchers to work on distributed quantum computing. The project aims to develop superconducting
-
optimization, with experience in adaptive routing and SDN technologies. Proficiency in programming languages such as Python, C/C++, and experience with parallel computing frameworks. Effective written and oral
-
We are seeking a highly motivated Postdoctoral Researcher with expertise in computational biology, deep mutational scanning data, and generative artificial intelligence (AI). The successful
-
We are seeking a Postdoctoral Appointee to work in the Mathematics and Computer Science (MCS) Division of the Computing, Environment, and Life Sciences directorate (CELS) of Argonne National
-
(e.g., Gaussian, ORCA) and periodic codes (e.g., VASP) is critical Considerable computational expertise in using quantum mechanical methods to calculate reaction mechanisms and kinetics in heterogeneous
-
Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
: Expertise in rare event simulation, deep learning, and developing computationally efficient approaches for simulation and modeling in complex systems is highly desirable Experience with parallel computing
-
Argonne’s core values of impact, safety, respect, integrity, and teamwork Preferred Skills and Qualifications: Experience with high-performance computing and parallel computing Familiarity with data
-
in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct
-
modeling of crystals, dislocation dynamics, and defect analysis, linking atomic-scale simulations to macroscopic properties. Familiarity or interest in machine learning methods and computing frameworks