Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
Job Summary Organization Overview The Facilities & Operations (F&O) Directorate’s mission is to support the science and technology and environmental restoration missions of the Laboratory by
-
administrative support. Essential Duties and Responsibilities: Provide overall leadership and direction of BNL’s occupational medicine program, including program development, administration, creation and
-
in support of the Lab’s industrial/OSHA safety program (e.g., Rigging, Lockout/Tagout, Confined Space, Fall Protection, Hazardous Materials/Hazwoper, etc. Create course content, training packages
-
concept through computer aided analysis, detailed 3D modeling and design, and system interface efforts. Deliver all phases of the project work – design, engineering analysis, R&D, procurement and
-
science with novel method development, and provides unique access to world-class computing resources, such as the BNL Institutional Cluster and DOE leadership computing facilities, as well as collaboration
-
Apply Now Job ID JR101748Date posted 03/21/2025 The Facilities & Operations (F&O) Directorate’s mission is to support the science and technology and environmental restoration missions
-
, collaboration, and respect for all. The engineer will split their time to support work planning and safety paperwork. Required Knowledge, Skills, and Abilities: BS in Electrical Engineering or related field
-
the department on new potential collaborations. Position Requirements: Required Knowledge, Skills, and Abilities: Ph.D. in computer science or a related field (e.g., engineering, applied mathematics, statistics
-
maintains an accredited personnel monitoring service, an instrumentation and calibration facility, and expertise in radiological engineering and nuclear materials management. The Radiological Control Division
-
. in computer science or a related field (e.g., engineering, applied mathematics, statistics) awarded within the last 5 years. Strong theoretical understanding and practical experience in deep learning