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Astronomy and Machine Learning Research Scientist
Physical Life Sciences | livermore, CA | 08/23/2022
Job Code: SES.3 Science & Engineering MTS 3 / SES.4 Science & Engineering MTS 4
Organization: Physical and Life Sciences
Position Type: Career Indefinite
Security Clearance: Anticipated DOE Q clearance (requires U.S. citizenship and a federal background investigation)
Drug Test: Required for external applicant(s) selected for this position (includes testing for use of marijuana)
Medical Exam: Not applicable
Join us and make YOUR mark on the World!
Are you interested in joining some of the brightest talent in the world to strengthen the United States’ security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.
We are committed to a diverse and equitable workforce with an inclusive culture that values and celebrates the diversity of our people, talents, ideas, experiences, and perspectives. This is essential to innovation and creativity for continued success of the Laboratory’s mission.
We have multiple openings for Astronomy and Machine Learning Research Scientists to join a vibrant team conducting research in astronomical surveys and machine learning methods across a broad mission space. You will pursue research in astronomical data analysis, machine learning algorithm development, and computational methods for applications to both scientific and national security programs. These positions are in the Physics Division/Applied Physics Section in the Astronomy and Astrophysics Analytics Group.
These positions will be filled at either the SES.3 or SES.4 levels based on knowledge and related experience as assessed by the hiring team. Additional job responsibilities (outlined below) will be assigned if hired at the higher level.
In this role you will
- Conduct astronomical data analysis, scientific data modeling, and data science research to include image and signal processing, Bayesian modeling, computational forward models, and uncertainty quantification.
- Develop and apply machine learning and artificial intelligence models for both scientific data analysis and surrogate modeling of computer simulations.
- Apply discrete event simulation and reinforcement learning tools and methods for systems analysis and autonomy applications.
- Develop software with adherence to professional best practices including using version control systems, test-driven and agile development practices, supporting deployment on multiple computing architectures, and open-source collaboration models.
- Effectively use available computing architectures for project execution, to include high-performance computing (HPC) and GPU-enabled systems.
- Conduct self-initiated research, maintain an awareness of technical literature in assigned areas, publish research results in peer-reviewed scientific or technical journals, and present results at external conferences, seminars, and/or technical meetings.
- Work as part of inter-disciplinary teams of scientists and engineers to achieve mission-oriented deliverables on externally driven timelines.
- Perform other duties as assigned.
Additional job responsibilities, at the SES.4 level
- Develop and lead new research projects based on accumulated scientific expertise, including pursuit of external funding opportunities.
- Lead the development of new mathematical, statistical, and machine learning models as needed to meet open-ended project goals.
- Lead project updates and briefings to sponsors, visitors to LLNL, and senior managers.
- Effectively manage and deliver impactful contributions to multiple simultaneous technical projects that may span different organizations across the lab.
- Mentor students, postdocs, and early-career staff in research and technical skills
- Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.
- PhD in Physics, Astronomy, or related field, or the equivalent combination of education and relevant experience.
- Research background in one or more of the following: optical astronomy survey analysis, development and application of machine learning and artificial intelligence models, development and application of statistical models, computational physics modeling, surrogate modeling of computer experiments, high-performance computing, discrete event simulation, or reinforcement learning.
- Ability to perform independent research, find innovative solutions and produce significant accomplishments to complex scientific and technical problems.
- Advanced verbal and written communication skills necessary to work in a multidisciplinary team environment, author technical and scientific publications, and deliver scientific presentations.
- Advanced interpersonal skills necessary to interact with a diverse set of scientists, engineers, and other technical and administrative staff.
Additional qualifications at the SES.4 level
- Significant experience initiating and leading scientific and technical research projects and teams and securing competitive funding for scientific research in the form of research grants or sponsored research projects.
- Extensive experience developing novel mathematical, statistical, or machine learning solutions to technical problems as evidenced by research publications or past technical project deliverables.
- Ability to manage multiple simultaneous projects and to engage productively with sponsors, visitors, and senior managers.
- Experience mentoring students, postdocs, or staff.
Qualifications We Desire
- Experience in software development as shown by open-source projects, scientific collaboration contributions, or an employment background that includes software engineering roles or responsibilities.
- Expertise with modern deep learning methods and software packages.
- Expertise with scientific computing workflow systems and deployment of data processing pipelines on various computing architectures.
- Significant experience working on a research team with individuals from diverse technical backgrounds, as well as an ability to function as an independent researcher with a high level of attention to details.
- Experience working in the U.S. national security community.
Additional InformationAll your information will be kept confidential according to EEO guidelines.
This is a Career Indefinite position. Lab employees and external candidates may be considered for this position.
Why Lawrence Livermore National Laboratory?
- Included in 2022 Best Places to Work by Glassdoor!
- Work for a premier innovative national Laboratory
- Comprehensive Benefits Package
- Flexible schedules (*depending on project needs)
- Collaborative, creative, inclusive, and fun team environment
Learn more about our company, selection process, position types and security clearances by visiting our Career site.
This position requires a Department of Energy (DOE) Q-level clearance. If you are selected, we will initiate a Federal background investigation to determine if you meet eligibility requirements for access to classified information or matter. In addition, all L or Q cleared employees are subject to random drug testing. Q-level clearance requires U.S. citizenship. For additional information, please see DOE Order 472.2.
Pre-Employment Drug Test
External applicant(s) selected for this position will be required to pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.
Equal Employment Opportunity
LLNL is an equal opportunity employer that is committed to providing candidates and employees with a work environment free of discrimination and harassment. We value and hire a diverse workforce as it is a vital component of our culture and success. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.
At LLNL, our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory. If you need a reasonable accommodation during the application or the recruiting process, please submit a request via our online form.
California Privacy Notice
The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.