Lawrence Berkeley National Lab’s (LBNL ) Applied Mathematics and Computational Research Division has an opening for a Computational Mathematics Postdoctoral Scholar to join the team.

The Scalable Solvers Group (SSG) in the Applied Mathematics and Computational Research Division (CRD) at the Lawrence Berkeley National Laboratory (LBNL) has a Computational Mathematics Postdoctoral Scholar opening in the area of numerical methods for quantum many-body problems. The SSG focuses mainly on developing scalable numerical algorithms and high performance implementations to enable scientific discovery through advanced computing (SciDAC). The Postdoc will participate in research activities related to the development of new mathematical formulations and algorithms for solving time-dependent quantum many-body problems away from equilibrium.

What You Will Do:

• Develop and analyze tensor network methods for solving large-scale eigenvalue problems and time-dependent quantum many-body problems.
• Develop efficient methods for optimization and time evolution on manifolds.
• Develop reduced order models and machine learning techniques for predicting the long-time dynamics of quantum many-body systems.
• Implement algorithms on the DOE leadership computing platforms consisting of CPUs and GPUs.

Additional Responsibilities as needed:

• Develop efficient algorithms for data reduction and analytics.
• Analyze algorithmic complexity and parallel scalability of new computational approaches.
• Interact with physical scientists to deploy algorithms in application software.

What is Required:

• Phd in Mathematics, Computer Science, Physical sciences (physics, chemistry and materials science), Computational Science or Engineering within the last 3 years.
• Knowledge of tensor decomposition method and tensor network algorithms such as density matrix renormalization group (DMRG), time evolution block decimation (TEBD) and the time dependent variational principle (TDVP) methods.
• Knowledge of numerical methods for solving large-scale eigenvalue problems and time dependent problems.
• The ability to program proficiently in a high-level programming language, such as C++/C/FORTRAN, and should have some experience in parallel computing and be able to use MPI and OpenMP.
• Ability to communicate effectively.
• Demonstrated ability to prepare research results for publication and presentation at seminars and scientific meetings.

Desired Qualifications:

• Knowledge of quantum many-body problems and various approximation models (Hartree-Fock, configuration interaction, coupled cluster, density functional theory, density matrix renormalization group/tensor networks).
• Knowledge of numerical optimization and/or time-evolution on manifolds.
• Knowledge of performance optimization for scientific software.
• Knowledge and experience with machine learning techniques is a plus.
• The ability to program on GPUs.

Want to learn more about Berkeley Lab's Culture, Benefits and answers to FAQs? Please visit: https://recruiting.lbl.gov/

The monthly salary range for this position is $6,431-$8,642 and is expected to start at $7,843 or above. Postdoctoral positions are paid on a step schedule per union contract and salaries will be predetermined based on postdoctoral step rates. Each step represents one full year of completed post-Ph.D. postdoctoral experience.

Notes:

• This is a full-time 2 year, postdoctoral appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds and ongoing operational needs. You must have less than 3 years of paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree.
• This position is represented by a union for collective bargaining purposes.
• This position may be subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
• Work will be primarily performed at: Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.

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