24 phd-in-architecture-landscape-built-environment Postdoctoral positions at Brookhaven Lab
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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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transport modeling and machine protection strategies for the EIC accelerator complex. This position will focus on Monte Carlo simulations to characterize the radiation environment resulting from beam losses
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the CFN scientific facilities: The CFN conducts research on nanomaterial synthesis by assembly designing precise architectures with targeted functionality by organizing nanoscale components. The CFN
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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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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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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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repository records, or other public communications. • You are committed to fostering an environment of safe scientific work practices. • You are committed to cultivating an inclusive and respectful workplace
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well as effectively in a collaborative team environment for solving scientific problems. Preferred Knowledge, Skills, and Abilities: Demonstrated experience in programming (e.g., Python). Experience in technologies
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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