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Berkeley Lab Hiring Computational Science Postdoctoral Fellow

 

The Scientific Computing Group in the Computational Research Division at Lawrence Berkeley National Laboratory (LBNL) has an immediate opening for a postdoctoral fellow to develop parallel and resilient algorithms for solving large sparse linear systems for the scientific areas that that are of interest to DOE and LBNL.

The candidate will participate in research projects to parallelize, optimize, and deploy new algorithmic variants of sparse direct solvers, algebraic multigrid solvers, and preconditioners. The research activities will include the analysis of the performance profile and algorithmic complexity of the new algorithms/codes; the improvement of the efficiency and resiliency of the existing algorithms/codes to hard (failure of a device) interrupts and soft (change of a data value) errors; and the development of novel algorithms on high performance computers for the scientific applications.  Targets of interest include supercomputers built from multi- and manycore processors.  Deliverables will include both prototype software distributions as well as publications targeted at top-tier research conferences.

KEY SUCCESS FACTORS:
  • PhD degree, within the last 3 years, in computer science, applied math, computational science or a related technical field is required.
  • Knowledge of parallel linear algebra and sparse matrix computations is highly desirable.
  • Experience in parallel programming in high-level languages, such as C/C++, MPI, and OpenMP.
  • Experience with performance analysis, modeling, and benchmarking for numerical algorithms and scientific codes.
  • Demonstrated ability to work independently as well as collaboratively in an interdisciplinary team contributing to an active intellectual environment.
  • Excellent written and oral communication skills.
 
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