130 python "Computer Vision Center" "Computer Vision Center" positions at Oak Ridge National Laboratory
Sort by
Refine Your Search
-
and maintain Python scripts, Arcade expressions, attribute rules, and automated processes (including batch scripts and Windows Task Scheduler jobs). Publish and manage map, feature, image, geoprocessing
-
, OpenMC, and/or MOOSE and familiarity with reactor systems and concepts. Programming/scripting experience including the use of one or more of C/C++, Python, Fortran, Git, and CMake an asset. Demonstrated
-
++, Python, Fortran, Git, and CMake an asset. Demonstrated writing and communication skills and ability to publish. Preferred Qualifications: Experience with Multiphysics software and simulations an asset
-
, MCNP, Serpent, OpenMC, and/or MOOSE and familiarity with reactor systems and concepts. Programming/scripting experience including the use of one or more of C/C++, Python, Fortran, Git, and CMake an asset
-
for the collection of in-situ mechanical testing data. Knowledge of scientific software in python (numpy, scipy, pandas) or related data analysis suite. Record of productive and creative research as demonstrated by
-
Enterprise Linux (RHEL) or Ubuntu, across physical and virtual environments and multiple security domains. Lead automation and infrastructure modernization using Ansible, Python, Bash, Git, and infrastructure
-
engineering and analysis to define hardware, software, storage, networking, and integration requirements. Develop prototypes, automation, scripts, and engineering solutions using technologies such as Python
-
and virtual Linux platforms across multiple security domains. Develop automation using Ansible, Python, Bash, and Git-based workflows to improve deployment, configuration, patching, compliance
-
utilization. Lead troubleshooting and root-cause analysis of complex HPC infrastructure and performance issues. Automation, Security & Modernization Develop and advance automation using Python, Bash, Ansible
-
Python and C or C++. Experience with parallel and distributed computing using technologies such as MPI, distributed machine-learning frameworks, and HPC workload managers. Experience using GPU-accelerated