Computational Scientist 2 - Richland, United States - Pacific Northwest National Laboratory

Pacific Northwest National Laboratory Richland, United States

1 week ago

Description

Responsibilities

Contribute to PNNL's goals in modeling and simulation of complex systems as part of the Laboratory's Computational Mathematics Group of the Advanced Computing, Mathematics, and Data Division (ACMDD). As a computational scientist, you'll join a talented, diverse team to make a scientific impact in predicting and controlling complex engineered and natural systems by developing multiscale and multiphysics models of these systems, employing advanced scientific machine learning tools to accelerate and enhance our current modeling capabilities, and deploying these models in high-performance computing environments.

Develop physics-based computational tools for modeling complex biological and energy systems with multiple spatial/temporal scales and various physical and chemical processes.

Apply advanced scientific machine learning methods to enhance our understanding and prediction capabilities of complex systems.

Develop and optimize high-performance numerical algorithms for large-scale scientific computing.

Interact, communicate, and solve problems with a diverse team of applied mathematics, computational science, and experimental research staff within the ACMDD group and across PNNL.

Publish your results in high-quality, peer-reviewed journals.

Present your research at technical conferences and project and program review meetings.

Participate in the development of research proposals.

Qualifications

Minimum Qualifications:

BS/BA and 2 years of relevant experience -OR-

MS/MA -OR-

PhD

Preferred Qualifications:

Ph.D. in Applied Mathematics, Computational Mechanics, or related Engineering areas with at least two years of postdoctoral experience.

Proficiency in statistical thermodynamics and dynamical systems.

Proficiency in network theory and simulating dynamics on networks.

Demonstrated proficiency in biological and chemical sciences. Specifically, demonstrated proficiency in simulating biological systems, from individual proteins to coupled chemical reactions in metabolism and large multiscale cell models; proficiency in interpreting biological -omics data and incorporating into simulation pipelines.

Experience developing high-performance parallel computing code for both CPUs and GPUs. Proficiency in developing scientific software using Python, GO, C/C++, and CUDA.

Proven track record in preparing manuscript submissions to scientific journals.

Additional demonstrated expertise in at least one of the following technical areas: (i) Multiscale/Multiphysics Modeling: (ii) Machine Learning: Use and development of physics-informed machine learning and reinforcement learning techniques for model reduction and conceptual system design. (iii) High-Performance Computing (HPC).

Hazardous Working Conditions/Environment

Not applicable

Additional Information

Not applicable

Testing Designated Position

This is not a Testing Designated Position (TDP)

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