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-informed machine learning (PIML) models for the prediction of physical and chemical properties using data from experiments and computation constrained by physics requirements. § Implementing algorithms
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. - Develop new nonlinear finite element models to address key data gaps in steel component behavior. - Translate findings into technical guidance that informs seismic design for damage control, post
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Computer/Information Sciences Internal Number: A-168130-3 General Description Professor Gillian Hadfield is seeking a highly-qualified postdoctoral scholar to join her team at the Normativity Lab in
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science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate administrative
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for an ultra-high vacuum synchrotron end-station using CAD software. - Run, optimize, and document data acquisition codes (LabVIEW and Python) - Aid NIST staff in developing plans
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Engineering, Mechanical Engineering, or a related field. § Ability to develop experimental apparatus using optics. § Ability to perform laboratory optical experiments. § Ability to analyze and model data
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oral and written communication in English language § Familiarity with scientific scripting languages. § Ability to develop prototypes of tools needed to analyze data. § Strong oral and written
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statistics. This collection of information is needed to facilitate the administrative functions of the PREP Program. Routine Uses: NIST will use the information collected to perform the requisite reviews
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at other institutions and research centers, as well as active involvement in the Hopkins Business of Health Initiative. Fellows will have access to existing datasets and are encouraged to engage in data
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Python and LabVIEW. - Experience in or desire to learn computer assisted design (CAD) software like SolidWorks. Application Instructions Please upload the following with your application