22 phd-in-architecture-interior-design-built-environment Postdoctoral positions at Brookhaven Lab
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dose Support the development of machine protection strategies through radiation environment modeling Collaborate with magnet, vacuum, and shielding engineering groups to evaluate and optimize design
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scientific facilities: The CFN conducts research on nanomaterial synthesis by assembly designing precise architectures with targeted functionality by organizing nanoscale components. The CFN researches and
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scientific facilities: The CFN conducts research on nanomaterial synthesis by assembly designing precise architectures with targeted functionality by organizing nanoscale components. The CFN researches and
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integrating physics requirements into the design of the EIC interaction region. The EIC group at BNL’s Physics Department has an opening for a Postdoctoral Research Associate. The selected candidate is expected
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on PCB layout designs and PCB/Detector assembly Participate in the testing and evaluation of custom-built and commercial radiation detection systems in the laboratory and at other experimental sites
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Knowledge, Skills, and Abilities: PhD in Chemistry, Physics, Biophysics, Biology, Biochemistry or Structural Biology. Proven ability to optimize peptide, protein or nucleic acid crystallization systems. Basic
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Required Knowledge, Skills, and Abilities: PhD in Accelerator Physics or a related field In-depth working knowledge of accelerator design codes such as BMAD, MADX, or ELEGANT Working knowledge of programming
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that incorporate latest machine-learning algorithms). Furthermore, the successful candidate will collaborate broadly with the other members of IO and CFN, leveraging their expertise in design and fabrication
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solutions to challenges influenced by meteorological conditions (contaminant dispersion, weather extremes, building design, renewable energy generation) in highly heterogeneous environments such as cities and
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computer science knowledge. Preferred Knowledge, Skills, and Abilities: Practical experience developing novel AI/ML algorithms and models. Knowledge about hardware architectures, compilers, neural network