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UID:submissions.supercomputing.org_SC23_sess503_job181@linklings.com
SUMMARY:Postdoctoral Researcher – Extreme Data Learning
DESCRIPTION:APPLY Online at:  https://nrel.wd5.myworkdayjobs.com/en-US/NRE
 L/job/Postdoctoral-Researcher---Extreme-Data-Learning_R11390\n\nThe Comput
 ational Sciences Center at NREL has an opening for a Postdoctoral Research
 er on a newly funded project on learning reduced models under extreme data
  conditions for design and rapid decision-making in complex systems. \n\nT
 he researcher will be part of a multi-institution and interdisciplinary te
 am that has funding through the DOE Office of Science Advanced Scientific 
 Computing Research Program. \n\nThe goal of the project is to leverage hig
 h-fidelity physics solvers to collect distributed and streamed data that a
 re informative about rare events and use this data to learn reduced models
  of physical phenomenon of interest to offshore wind. \n\nThe postdoctoral
  researcher will work with NREL staff and external collaborators on develo
 ping algorithms and tools for a paradigm of data-driven modeling of comput
 ational fluid dynamics (CFD) representative of wind farm physics. The resp
 onsibilities for this position include:\n\n·       Developing in situ pipe
 lines to handle vast volumes of data (in the terabyte range) streamed by N
 REL's advanced wind farm physics modeling software,\n\n·       Developing 
 active data acquisition techniques that can collect data in regions of rar
 e events,\n\n·       Applying dimensionality reduction techniques for data
  analysis of large-scale turbulent flows,\n\n·       Learning reduced mode
 ls of turbulent flows using streamed and distributed data,\n\n·       Phys
 ical correction of reduced models using statistical and machine learning t
 echniques.\n\nIn addition, the successful candidate will be able to work i
 ndependently, as well as in a large collaborative team with researchers fr
 om NREL, academia, and other national laboratories. Join our dynamic team 
 and help build the future of wind energy simulations on the next generatio
 n of supercomputers.\n\n
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