130 algorithm-development-"Prof"-"Washington-University-in-St"-"Prof" positions at Brookhaven Lab
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the development and production of isotopes that are critical to our Nation’s prosperity and security, including life-changing radioisotopes that have shown amazing promise as therapeutics against aggressive cancers
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efficient resource allocation, overseeing the development and coordination of preventative maintenance, as well as collecting and analyzing data to develop key performance metrics that drive continuous
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development. The group leader will manage a team of magnet engineers and scientists. Essential Duties and Responsibilities: Plan and lead accelerator magnet development projects in response to the needs
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at Brookhaven National Laboratory (BNL) is seeking a Training Specialist to join the Radiological Control Division. This position will be responsible for the development and delivery of technical training
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of responsibility. Develops, implements and updates internal procedures. Leads teams and frequently exercises work discretion. Required Knowledge, Skills, and Abilities: BA or BS degree in a business field, plus six
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starters/VFD, etc. Analyze complex engineering problems and offer effective and efficient resolutions to management/project manager in a timely manner while working on several projects at once. Development
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development and is the nexus of a broad collaboration network. Each year, CFN staff members support the research of nearly 600 external facility users. Three strategic nanoscience themes underlie the CFN
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, approve, and track all payments and contract items for all water sampling services Develop slides for PowerPoint presentations Maintain and create yearly shift worker calendars Perform administrative
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studies and computer simulations Collaborate with the BMAD development team at Cornell University by implementing new features into the code Participate in the EIC design effort in a more general sense
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., crowd sourced data or from mobile and distributed instrument networks) Assess the performance of next-generation predictive urban climate models using observations Develop new visualization strategies