Computational Materials Science Postdoctoral Fellow
Lawrence Berkeley National Laboratory
DescriptionLawrence 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.
RequirementsWhat 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.
Company DescriptionBerkeley Lab is committed to Inclusion, Diversity, Equity and Accountability (IDEA, and strives to continue building community with these shared values and commitments. Berkeley Lab is an Equal Opportunity and Affirmative Action Employer. We heartily welcome applications from women, minorities, veterans, and all who would contribute to the Lab's mission of leading scientific discovery, inclusion, and professionalism. In support of our diverse global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.
Event Type
Job Posting
TimeWednesday, 16 November 202210am - 3pm CST
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