Computational Material Sciences Postdoctoral Researcher

Lawrence Berkeley National Lab's (LBNL) Computational Research Division has an opening for a Computational Material Sciences Postdoctoral Researcher to join the team.

In this exciting role, you will focus mainly on developing scalable numerical algorithms and high performance implementations to enable scientific discovery through advanced computing. 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 multiscale models and fast and reliable quantum embedding methods.
• Develop efficient impurity solvers for time-dependent quantum systems.
• Develop efficient algorithms solving the Kandonoff-Baym nonlinear integral differential equations (KBEs).
• Develop reduced order models and machine learning techniques for predicting the long term dynamics of quantum many-body systems through the time-dependent Green's function formalism.
• 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:

• Requires a Ph.D in Mathematics, Computer Science, Physical sciences (physics, chemistry and materials science), Computational Science or Engineering within the last 3 years, with a strong background in computational chemistry, computational physics or materials science.

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 the Green's function formalism for modeling properties of quantum many-body systems.
• The ability to program proficiently in a high-level programming language, such as C++/C/FORTRAN, and should have experience in parallel computing and be able to use MPI and OpenMP.
• Familiar with electronic structure, molecular dynamics and Monte Carlo software tools.
• Ability to communicate effectively.
• Demonstrated ability to prepare research results for publication and presentation at seminars and scientific meetings.
• Knowledge of performance optimization for scientific software.
• Knowledge and experience with machine learning techniques is a plus
• The ability to program on GPUs.

Notes:

• This is a full-time 1 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 4 years 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.
• Salary will be predetermined based on postdoctoral step rates.
• 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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