Lawrence Berkeley National Lab’s (LBNL) Applied Math and Computational Sciences Division has an opening for a Computational Materials Science Postdoctoral Fellow to join the team.

In this exciting role, you will be responsible for research focused on developing novel new algorithms and efficient HPC implementations in first principle electronic structure materials science and chemistry applications. The developments will be focused in reduced-scaling methods for ground and excited state approaches including the random-phase approximation (RPA), GW method, and real-time time-dependent density functional theory (RT-TDDFT) with physically tuned hybrid functionals. In addition, this position will contribute to the development and/or advancement of open-source software tools. Involvement in the publication of the research and contributions at conferences is expected.

The position will be part of an integrated team of computational materials scientists, chemists, physicists and HPC application developers that will design and deliver novel approaches, methodologies, algorithms and software to tackle large scale ground and excited state first principles materials simulations and scaling efforts to future leadership class HPC Exascale architectures.

What You Will Do:

• Contribute to the development of new, novel and scalable algorithms for preexa- and exascale platforms in the area of computational physics, chemistry and materials science, with a focus on ground and exited state methods based on the random-phase approximation (RPA and GW) and real-time time-dependent density functional theory (RT-TDDFT) employing hybrid functionals.
• Contribute to the development of new, novel methods and approximations to reduce the computational complexity and scaling with system size of methods based on random-phase approximation (RPA and GW).
• Document work and results in the form of journal papers and conference proceedings.
• Present work and results at scientific meetings and conferences.
• Manage development effort for large scientific applications at the lab.
• Contribute to the development of new, novel and scalable algorithms for preexa- and exascale platforms in the area of computational physics, chemistry and materials science, with a focus on ground and exited state methods based on the random-phase approximation (RPA and GW) and real-time time-dependent density functional theory (RT-TDDFT) employing hybrid functionals.
• Contribute to the development of new, novel methods and approximations to reduce the computational complexity and scaling with system size of methods based on random-phase approximation (RPA and GW).
• Document work and results in the form of journal papers and conference proceedings.
• Present work and results at scientific meetings and conferences.
• Manage development effort for large scientific applications at the lab.

What is required::

• PhD degree in Computational Materials Sciences, Computational Chemistry and Physics, or a relevant field is required.
• Strong fundamentals in computational materials sciences / chemistry methods for systems in the condensed phase.
• Demonstrated experience in applying computational physics methodologies to materials science problems including many-body perturbation theory and hybrid density functional theory algorithms and codes.
• Demonstrated ability to participate in and provide intellectual leadership to a cross-disciplinary team.
• Excellent written and oral communication skills.
• Knowledge of Python, Fortan, C, MPI, OpenMP, and other parallel programming models.
• Experience in programming GPU-accelerated architectures.
• Experience with HPC application profiling/optimization methodologies.
• Experience with HPC application debugging techniques and tools.

Notes:

• This is a full-time 2 years 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.
• Salary will be predetermined based on postdoctoral step rates.
• This position will be remote initially, but limited to individuals residing in the United States tentatively until 2021 due to COVID-19. Once the Bay Area shelter-in-place restrictions are lifted, work will be primarily performed at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.

Based on University of California Policy - SARS-CoV-2 (COVID-19) Vaccination Program, Berkeley Lab strongly recommends that all members of our community obtain the COVID-19 vaccine as soon as they are eligible. As a condition of Physical Presence at a Berkeley Lab Location, all Covered Individuals must Participate in the COVID-19 Vaccination Program by providing proof that vaccination requirements have been met or submitting a request for Exception or Deferral.

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