106 assistant-and-professor-and-computer-and-science-and-data uni jobs at Brookhaven Lab
Sort by
Refine Your Search
-
the equivalent tools associated with the EIC Project scope. Required Knowledge, Skills, and Abilities: BA/BS Degree (or equivalent experience), preferably in Computer Science or a related discipline At least ten
-
are conducted in compliance with BSA’s Prime Contract, applicable statutes and regulations, and in accordance with the highest ethics and standards. Oversight of BNL Property Management Program to effectively
-
this position but does include the major elements in the job. Preferred Knowledge, Skills, and Abilities: • Experience using a maintenance management system or CMMS program. • Familiarity with Building Management
-
qualification evaluation: Experience with the Incident Command System. Knowledge of basic computer skills. Environmental, Health, and Safety Requirements: Medical/physical requirements : Successfully pass a pre
-
technology. Experience with analyzing data, advanced Excel skills or other tools used for analysis. Analytical mindset with the ability to spot trends, inconsistencies, and areas for improvement. Strong
-
program, and oversight of BNL’s Employee Assistance Program (EAP) contractor. In accordance with the protocols established for both the Emergency Medical Service for the fire service and the Protective
-
documents. Ability to sufficiently write/complete work orders and other required documents. Ability to communicate verbally with customers, fellow workers and supervisors Possess basic computer skills. Must
-
procedures. Working knowledge of computers and software applications. Possess good written and verbal communication skills, including: Ability to sufficiently write/complete work orders and other required
-
knowledge of computers and software applications. Possess good written and verbal communication skills, including: Ability to sufficiently write/complete work orders and other required documents. Ability
-
Nanomaterial Discovery, integrating synthesis, advanced characterization, physical modeling, and computer science to iteratively explore a wide range of material parameters. The CFN develops and utilizes