65 structures "https:" "https:" "https:" "UCL" uni jobs at Oak Ridge National Laboratory
Sort by
Refine Your Search
-
-on construction of mission equipment Prepare basic engineering calculations following standard methods and principles used in similar engineering analysis. Utilize and develop an understanding of industry codes and
-
visit https://www.ornl.gov/directorate/isotopes for more information about ISED. About ORNL: As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year
-
supplies throughout ORNL in a safe and efficient manner. Operate construction, excavation and power equipment such as high lifts, dozers, bob-cats, back hoes, road grader, etc. Comprehend crane load charts
-
and legacy document collections across the data lifecycle, from acquisition and documentation through preservation and reuse. Organize, curate, and enrich structured and unstructured datasets, including
-
. Reports may include total payroll results and analysis of pay components. Analyze requests for possible changes that have occurred in report structure or requirements. Reconcile reporting to general ledger
-
Coordinating design with STS Structural Engineers to ensure seismic qualification of cabling supports where required by code Interfacing with Installation Coordinators during the installation of cables and
-
information. Effective written and verbal communication skills. Analytical mindset with interest in workforce data and reporting. Ability to manage multiple priorities in a structured, deadline-driven
-
. Provide input to HFIR 3-Year planning activities and updates. CONFIGURATION MANAGEMENT Prepares engineering designs for new installations and for replacement and upgrade of reactor structures, systems, and
-
strength of ORNL which is the U.S. Department of Energy’s largest Office of Science laboratory. ORNL is home to two user facilities in manufacturing – the Manufacturing Demonstration Facility (https
-
fuels and structural materials application space, working collaboratively with other scientists. Apply machine learning and artificial intelligence tools to innovate in particle fuels characterization