Berkeley Lab's Computational Science Department has immediate openings for multiple Computer Systems Engineers to assist in the implementation and documentation of new high-performance computing (HPC) approaches to a variety machine learning challenges in the Physics Sciences.
Over the course of the last five years, Berkeley Lab's Computational Research Division in collaboration with NERSC Data Analytics group and the Physics Division has developed a researchprogram in data-driven pattern recognition algorithms for High Energy Physics (HEP) and Cosmology, targeting massively parallel and post-Moore architectures (including neuromorphic and quantum systems). Several promising research directions involve the development of distributed Geometric Deep Learning, algorithms based on distributed graph neural networks, as well as Generative Adversarial Networks.
The selected candidates will be hired at the CSE 1, 2, or 3 level. Classification will depend upon the candidate's level of skills, knowledge, and abilities.
The Computer Systems Engineer will:
In the context of the DOE ExaLearn Co-Design Center, collaborate with LBNL physicists and computer scientists to support development of innovative distributed pattern recognition algorithms for the next generation of HEP and Cosmology experiments and simulations on HPC systems.
Develop workflows for distributed training and optimization of neural networks, GANs and regression algorithms as we push to Exascale.
Profile and benchmark deep learning codes to identify data management, I/O, and overall workflow bottlenecks.
Implement and tune software solutions to address bottlenecks in deep learning frameworks, I/O middleware, and file system parameters on current HPC systems.
Run performance tests on multiple DOE HPC systems, such as Summit @ ORNL and Cori @ LBNL, to characterize the effectiveness of solutions created.
Work on and troubleshoot problems of moderate scope where analysis of situations or data requires a review of a variety of factors.
Contribute to one or more existing research projects dedicated the development of Machine Learning algorithms for Cosmology and HEP.
In addition to the duties outlined above
At the CSE2 level
Apply professional experience and work at higher level of independence when completing assignments.
Work on and troubleshoot problems of diverse scope where analysis of data requires evaluation of identifiable factors.
At the CSE3 level
Apply wide-ranging experience and expertise to determine methods and procedures on new assignments and may coordinate activities ofother personnel.
Work on and troubleshoot complex issues where analysis of situations or datarequires an in-depth evaluation of variable factors.
Contribute to one or more existing research projects dedicated the development of MachineLearning algorithms for Cosmology and HEP.
Requires a Bachelor's degree and 2 years related experience (or higher degree) or equivalentexperience.
Background in I/O middleware, including familiarity with multiple storage architectures and technologies.
Knowledge of and some basic experience with GPGPU programming.
Familiarity with performance profiling, benchmarking, optimizing, and/or scaling applications on HPC systems.
Strong programming ability - preferably in Python, C, and/or C++
Strong oral and written communication skills.
Demonstrated ability to work effectively as part of a cross-disciplinary team.
In addition to the qualifications outlined above
At the CSE2 level
Requires a Bachelor's degree and 5 years related experience (or higher degree) or equivalentexperience.
Experience in I/O middleware, including familiarity with multiple storage architectures and technologies.
Demonstrated experience with GPGPU programming.
Knowledge and experience with performance profiling, benchmarking, optimizing, and/or scaling applications on HPC systems.
Ability to troubleshoot diverse problems and resolve a wide range of issues in creativeways.
at the CSE3 level
Requires a Bachelor's degree and 8 years related experience (or higher degree) orequivalent experience
Demonstrated experience in I/O middleware, including familiarity with multiple storage architectures and technologies.
Demonstrated expertise with GPGPU programming.
Demonstrated skill and expertise with performance profiling, benchmarking, optimizing, and/or scaling applications on HPC systems.
Ability to apply professional concepts and company objectives to resolve complex issues in creative and effective ways.
Additional Desired Qualifications:
A PhD in computer science, physics, or related fields.
Experience, knowledge and / or significant interest in applying I/O middleware optimizations to scientific data.
Experience, knowledge, and/or significant interest in applying multiple machine learning techniques to scientific data
Experience or interest in HEP computing, cosmology data analysis, cosmological simulation
Background and experience in computational methods and scientific computing.
Experience in software performance evaluation and optimization
Knowledge of HPC systems
The posting shall remain open until the position is filled, however for full consideration, please apply by close of business on September 29, 2019.
This is a full time career appointment.
Classification will depend upon the applicant's level of skills, knowledge, and abilities.
Full-time, M-F, exempt from overtime pay (monthly paid).
Salary is commensurate with experience.
This position is contingent on the successful completion of a background check.
Work will be primarily performed at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.
Berkeley Lab (LBNL) addresses the world's most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab's scientific expertise has been recognized with 13 Nobel prizes. The University of California manages Berkeley Lab for the U.S. Department of Energy's Office of Science.
Equal Employment Opportunity: Berkeley Lab is an Equal Opportunity/Affirmative Action Employer. All qualified. applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status. Berkeley Lab is in compliance with the Pay Transparency Nondiscrimination Provision under 41 CFR 60-1.4. Click here to view the poster and supplement: "Equal Employment Opportunity is the Law."
Internal Number: 86111
About Lawrence Berkeley National Laboratory
In the world of science, Lawrence Berkeley National Laboratory (Berkeley Lab) is synonymous with excellence. Thirteen scientists associated with Berkeley Lab have won the Nobel Prize. Fifty-seven Lab scientists are members of the National Academy of Sciences (NAS), one of the highest honors for a scientist in the United States. Thirteen of our scientists have won the National Medal of Science, our nation's highest award for lifetime achievement in fields of scientific research. Eighteen of our engineers have been elected to the National Academy of Engineering, and three of our scientists have been elected into the Institute of Medicine. In addition, Berkeley Lab has trained thousands of university science and engineering students who are advancing technological innovations across the nation and around the world. Berkeley Lab is a member of the national laboratory system supported by the U.S. Department of Energy through its Office of Science. It is managed by the University of California (UC) and is charged with conducting unclassified research across a wide range of scientific disciplines. Located on a 200-acre site in the hills above the UC Berkeley campus that offers spectacular... views of the San Francisco Bay, Berkeley Lab employs approximately 4,200 scientists, engineers, support staff and students. Its budget for 2011 is $735 million, with an additional $101 million in funding from the American Recovery and Reinvestment Act, for a total of $836 million. A recent study estimates the Laboratory's overall economic impact through direct, indirect and induced spending on the nine counties that make up the San Francisco Bay Area to be nearly $700 million annually. The Lab was also responsible for creating 5,600 jobs locally and 12,000 nationally. The overall economic impact on the national economy is estimated at $1.6 billion a year. Technologies developed at Berkeley Lab have generated billions of dollars in revenues, and thousands of jobs. Savings as a result of Berkeley Lab developments in lighting and windows, and other energy-efficient technologies, have also been in the billions of dollars. Berkeley Lab was founded in 1931 by Ernest Orlando Lawrence, a UC Berkeley physicist who won the 1939 Nobel Prize in physics for his invention of the cyclotron, a circular particle accelerator that opened the door to high-energy physics. It was Lawrence's belief that scientific research is best done through teams of individuals with different fields of expertise, working together. His teamwork concept is a Berkeley Lab legacy that continues today.