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The Naval Nuclear Laboratory is operated for the U.S. Department of Energy (DOE) by Fluor Marine Propulsion, LLC (FMP), a wholly owned subsidiary of Fluor Corporation. - Naval or commercial nuclear plant operational or design experience.
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Naval Nuclear Laboratory personnel are FMP employees who work at four DOE facilities: Bettis Atomic Power Laboratory, Knolls Atomic Power Laboratory, Kenneth A. Kesselring Site, and Naval Reactors Facility, and at the U.S. Department of Defense-owned Nuclear Power Training Unit-Charleston.
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1+ years of experience in advanced data analysis (using JMP, GAJT and/or SQL), statistical process control (SPC), and design of experiment (DOE) principles. Employees in the Technology Development and Manufacturing Group are part of a worldwide network of design, development, manufacturing, and assembly/test facilities, all focused on utilizing the power of Moore’s Law to bring smart, connected devices to every person on Earth.
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Familiar with DOE and Savannah River Site engineering standards. Our client supports NNSA Federal Project Directors with technical advice, innovative or alternate approaches, and oversight of contractor and supplier quality performance in the areas of design, procurement, construction, commissioning, monitoring, and reporting.
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APTIM is seeking an experienced Project Engineer to provide leadership and direction for design projects funded by the U.S. Department of Energy. Provides direction and oversight to the architectural and engineering design leads on an assigned project.
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Executes Design of Experiments (DOE) and Proven Acceptable Range (PAR) experiments to support design space understanding and process validation as they relate to oligonucleotide synthesis, process chromatography, and other purification and isolation techniques.
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Ultimately, a top-notch data modeler should be able to design models that are atomic, reduce data redundancy, streamline data movements, and reduce TCO. This requires maintaining a positive and collaborative working relationship with teams within DOE as well as with wider Aladdin developer community.
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Work with simulation teams to set up tests and analyze results related to structural integrity and design life. Independently manage design engineering responsibilities for assigned projects.
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Strong statistical skills include but not limited to statistical process control (SPC), capability analysis, linear regressions, categorical data analysis and design of experiment (DOE.
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Job Description As a Silicon Photonics (SiP) Process Integration Engineer, you will be part of Intel's SiP Process Development and Manufacturing (SPDM) team that is leading Intel's market transition and driving innovation for the next generation of optical interconnect products.
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Location Description: Michael Foods, Inc. located in Klingerstown, Pennyslvania known for their ice cream socials at Klingerstown Lutheran Parish, fishing rodeo, and fireman's parade. Welding, sanitary welding, pipe fitting, soldering, rigging application and use of mechanical tools, hand tools, and power tools and machine shop to machine within specific tolerance using various measuring equipment.
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Experience with experimental design& planning, assay development, statistics, DOE techniques, data analysis methods and software (JMP, Python, or Matlab preferred). You will design and develop thoughtful DOE and testing protocols conducive to generation of rapid insights on structure-function behavior and design optimization.
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If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
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Using statistical design of experiments (DOE) to optimize bioconjugation processes including conjugation reactions, purification operations, and analytical characterization. Working at the bench to design and develop scalable, robust and controlled GMP-ready bioconjugation and purification processes.
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Working knowledge of statistical methods for DOE design and data analysis, statistical process control (SPC), multivariate analysis (MVA), and/or process analytical technologies (PAT) techniques for manufacturing processes.
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