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Postdoctoral Appointee - Modeling & Optimization Methods for Constrained Ph

Title:  Postdoctoral Appointee - Modeling & Optimization Methods for Constrained Ph Date Posted:  08/22/2013
Division:  Mathematics and Computer Science Date Re-posted:  
Requisition:  321235 MCS Salary:  4586-7644
Employment Category:  Temporary Pay Cycle:  Monthly
Shift:  8:30am - 5:00pm Grade:  700
Hours:  40  
Job Description
  Basic Purpose
  Will produce new nonlinear optimization models and scalable algorithms for solving large-scale inverse problems arising from diffractive imaging data. We will directly model and solve structured phase retrieval problems, which involve Fourier/inverse Fourier and related transforms. Modeling efforts will focus on addressing both scientific goals and the challenges of data produced at world-class light source facilities. Classes of models/methods that the project will explore include stochastic optimization, robust optimization, and global optimization based on conic relaxations.
  Knowledge, Skills and Experience
Considerable knowledge in optimization, nonlinear inverse problems, or numerical analysis. Considerable expertise in Octave/Matlab/Python/C/C++/Fortran.
Good collaborative skills, including the ability to work well with other divisions, laboratories and universities. Good communication skills. Good knowledge of fundamentals of probability/statistics.
Candidates should have a Ph.D. in mathematics, computer science or a related discipline.
  Minimum Education/Experience Requirements
Years Since Ph.D. -- 0-1, 1-2, 2-3

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