Machine Learning Researcher

We have an opening for a Machine Learning Expert to contribute to fundamental R&D in machine learning and statistical methods in support of a new project on “Terraforming Soil”.  This interdisciplinary project aims to develop agricultural solutions for climate change mitigation.  In this role you will lead efforts to develop new multi-fidelity representation learning models to analyze large collections of soil spectra, infer important chemical markers, and account for uncertainties in the process. You will work with or lead multi-disciplinary teams consisting of machine learning experts and domain scientists.  You will also have the opportunity develop and lead independent research thrusts and engage with a variety of related research projects in parallel computing, data analysis and visualization, or applied mathematics applied to a variety of national security problems.  This position is in the Center for Applied Scientific Computing (CASC) Division within the Computing Directorate

You will 

• Research, develop, implement, and evaluate new machine learning techniques for multiple applications in a collaborative scientific environment.
• Actively participate with project scientists and engineers in defining, planning, and formulating experimental, modeling, and simulation efforts for complex problems stemming from national security applications.
• Provide guidance to subject matter experts in various fields to jointly explore the potential for machine learning research to solve domain-specific challenges.
• Adapt current machine learning research to real-world applications at scale, with potentially limited and noisy data, with a high consequence of error, and guide the development of practical solutions.
• Present and disseminate research results at scientific conferences and in peer-reviewed publications.
• Establish future research directions and author grant proposals including presentations to programmatic sponsors and external funding agencies.
• Collaborate with a broad spectrum of scientists and engineers, both internally and externally, to accomplish research goals.
• Perform other duties as assigned.

• Ph.D. in Computer Science, Applied Mathematics, Statistics or related field or the equivalent combination of education and related experience.
• Significant experience in at least one machine learning research area, such as multimodal modeling, representation learning, safety & robustness, uncertainty quantification, interpretability, physics-constrained ML, or graph-based learning.
• Significant experience developing, implementing, and applying advanced statistical or machine learning models and algorithms using modern software libraries such as PyTorch, TensorFlow, or similar as evidence through medium to large scale deep learning models and experiments.
• Demonstrated research productivity, as documented by publications, reports, presentations, and/or open-source software in high impact AI/ML focused venues, such as, NeurIPS, ICML, ICLR, CVPR, AAAI, AISTATS, UAI, KDD, or JMLR.
• Significant experience in working with diverse teams to solve complex problems and deliver practical solutions for environmental or climate applications.
• Advanced verbal and written communication skills necessary to interact with a multi-disciplinary research team, author technical and scientific reports and papers, and deliver scientific presentations.
• Advanced analytical and problem-solving skills necessary to craft creative solutions and solve complex problems.

Qualifications We Desire

• Experience with high-performance computing, GPU programming, parallel programming, cloud computing, and/or related methods including running numerical simulations or complex workflows
•  Experience in working with subject matter experts in one or more areas, such as physics, biology, or engineering.
• Experience or interest in climate security topics such as a direct carbon capture.

All your information will be kept confidential according to EEO guidelines.

Position Information

This is a Flexible Term appointment, which is for a definite period not to exceed six years.  If final candidate is a Career Indefinite employee, Career Indefinite status may be maintained (should funding allow).

Why Lawrence Livermore National Laboratory?

• Included in 2024 Best Places to Work by Glassdoor!
• Flexible Benefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules (*depending on project needs)
• Inclusion, Diversity, Equity and Accountability (IDEA) - visit https://www.llnl.gov/diversity
• Our core beliefs - visit https://www.llnl.gov/diversity/our-values 
• Employee engagement - visit https://www.llnl.gov/diversity/employee-engagement

Security Clearance

None required.  However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process.  This process includes completing an online background investigation form and receiving approval of the background check.  (This process does not apply to foreign nationals.) 

Pre-Employment Drug Test

External applicant(s) selected for this position must 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.

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To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf

Equal Employment Opportunity

We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. 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.

We invite you to review the Equal Employment Opportunity posters which include EEO is the Law and Pay Transparency Nondiscrimination Provision.

Reasonable Accommodation

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 use our online form to submit a request. 

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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.