Term Computer Systems Engineer | Lawrence Berkeley National Laboratory

Location

Berkeley, CA | United States

Job description

Berkeley Lab's Applied Mathematics and Computational Research Division has an opening for a Computer Systems Engineer 3 (CSE 3) position developing novel data-driven reduced models and surrogate models for atmospheric and fusion simulations. You will be part of the Applied Computing for Scientific Discovery Group, which has a focus on enabling scientific discovery through the development of advanced software applications, tools, and libraries in key DOE mission areas, as well as the development of scientific computing applications and capabilities for the integration and analysis of complex data from simulation and experiment. In this position, you will play an integral role in a multidisciplinary team that includes scientists from energy technologies, physical sciences, and computational sciences. You will actively contribute to ACSD's efforts in machine learning, optimization, and surrogate model development to enable scientific insights from climate and fusion simulations.

This position is a research position combining elements of applied mathematics, optimization, surrogate modeling, statistics, machine learning, and computational science. The successful applicant will develop, test, and benchmark new optimization models, active learning and surrogate model strategies. A strong background in high performance computing and programming is highly desired.

What You Will Do:

• Perform in-depth research in data-driven reduced order models, novel data representations and diagnostics for fusion and climate models.
• Lead the development of surrogate models to represent aerosol microphysics processes in the context of climate simulations.
• Design and study the representation of diagnostic variables in a reduced-order manner to inform physical understanding of these processes.
• Use transfer learning and/or data-driven reduced order modeling to develop surrogate models for fusion simulations.
• Deploy developments in larger HPC-enabled models.
• Work productively in a multidisciplinary team environment.
• Author peer-reviewed journal articles and contribute to research proposals.
• Publish developed algorithms as software packages.
• Work on and resolve complex issues where analysis of situations or data requires an in-depth evaluation of variable factors.
• Exercise judgment in selecting methods, techniques and evaluation criteria for obtaining results.
• Determine methods and procedures on new assignments and may coordinate activities of other personnel.
• Network with key contacts outside your own area of expertise.

What is Required:

• Typically requires a minimum of 8 years of related experience with a Bachelor's degree in Applied Mathematics, Physics, Mechanical Engineering, Computer Science, or a related field; or 6 years and a Master's degree; or equivalent combination of education and experience.
• Demonstrated research experience in the development and application of data-driven and surrogate models for high-dimensional physical systems.
• Demonstrated expertise in Python programming.
• Demonstrated experience working on high performance computing.
• Demonstrated ability and desire to work as part of an energetic cross-disciplinary team.
• Excellent oral and written communication skills.
• Strong interpersonal communication skills.
• Ability to resolve complex issues in creative and effective ways.
• Ability to network and collaborate with key contacts outside their own area of expertise.

Requested Application Materials:

• Curriculum Vitae
• Detailed Cover Letter

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Notes:

• This is a full time, 1 year, term appointment with the possibility of extension or conversion to Career appointment based upon satisfactory job performance, continuing availability of funds and ongoing operational needs.
• This full salary range of this position is between $10,575 to $17,845 per month and is expected to pay between a targeted range of $11,896 to $14,540 per month depending upon candidates' full skills, knowledge, and abilities, including education, certifications, and years of experience.
• 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 may be performed on-site, hybrid, full-time telework. The primary location for this role is Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA. Work must be performed within the United States.

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.

Equal Opportunity and IDEA Information Links:

Know your rights, click here for the supplement: Equal Employment Opportunity is the Law and the Pay Transparency Nondiscrimination Provision under 41 CFR 60-1.4.

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