Sort by
Refine Your Search
-
offered a salary at or near the top of the range for a position. Link to benefits. https://jobs.ornl.gov/content/Benefits/?locale=en_US Overview: The Information Technology Services Directorate at the Oak
-
Research Code of Conduct. Our full code of conduct, and a statement by the Lab Director's office can be found here: https://www.ornl.gov/content/research-integrity Basic Qualifications: BS degree in
-
. Formulating necessary solutions using various parallel computing paradigms and tools, HPC schedulers (such as slurm), Containers and Kubernetes, Python, Bash and other scripting/programming languages in
-
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
-
, Python, Bash, and GitLab CI. Support the use and understanding of in-house Kubernetes operators and serve as a secondary maintainer for those controllers. Hardware and Infrastructure Management Write and
-
Qualifications: Ph.D. (within 0–5 years) in computational bioscience, computational biophysics, computer science, or a related field Strong programming skills in C++, Python, or similar scientific computing
-
, or closely related field Strong computational skills with modeling and simulation experience using High Performance Computing environments and experience with Linux environments Experience with MATLAB, Python
-
systems, including embedded C, C++, Python, Linux, and software testing. A high level of facility with MS Office products including Word, Excel, Power Point and Teams is required. Excellent written and oral
-
in Python and C++ programming Ability to get and hold a security clearance A commitment to lifelong learning Preferred Qualifications: 5 or more years of experience relevant to the job duties
-
, Environmental Informatics, or a closely related field. 3+ years of strong programming experience in Python (including data processing, scripting, or basic ML workflows). Foundational understanding of ML concepts