Computational Chemistry Postdoctoral Researcher

Lawrence Berkeley National Lab's (LBNL) Computational Research Division has an opening for a Computational Chemistry Postdoctoral Researcher - Employee 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 performing large-scale electronic structure calculations and molecular simulations required to model chemical reaction and dynamics of rare events for non-equilibrium systems using a variety of computational approaches.

What You Will Do:

• Develop efficient algorithms for solving the Kohn-Sham density functional theoy eigenvalue problem.
• Apply low rank approximation techniques such as the interpolative separable density fitting (ISDF) method to reduce the computational complexity of highly accurate electronic structure methods.
• Study and compare a variety of methods such as dynamic mode decomposition, diffusion map and sketchmap for computing chemical reaction coordinates.
• Develop deep reinforcement learning based methods for transition path sampling.
• 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 the 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.
• Knowledge of chemical reaction, e.g. transition state theory, molecular dynamics and Monte Carlo simulation.
• 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.

Desired Qualifications:

• Knowledge of performance optimization for scientific software.
• Knowledge and experience with machine learning techniques is a plus.
• The ability to program on GPUs.

Notes:

• Postdoctoral Scholars - This is a full-time1 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 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.

Berkeley 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.

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