Los Alamos National Laboratory Machine Learning at Scale for Computational Materials Postdoc in Los Alamos, New Mexico
What You Will Do
The Applied Computer Science Group (CCS-7) at Los Alamos National Laboratory is seeking qualified applicants for a postdoctoral position. The candidate will be expected to perform outstanding research at the intersection of high-performance computing, machine learning, physics, and chemistry. The members of the CCS division, who would sponsor the postdoctoral associate, are experts in high performance computing and machine learning techniques for the simulation of materials.
The postdoctoral researcher will collaborate with staff members, postdocs, and graduate students in a variety of groups, including Information Sciences (CCS-3) and Physics and Chemistry of Materials (T-1), seeking to understand and model the properties of matter at the atomic level. Specifically, the postdoctoral researcher will develop workflows and modeling techniques in high-performance computing and machine learning to construct high-accuracy, machine-learning based interatomic potentials, that will facilitate large-scale simulations of chemical and materials systems on world-class high-performance computers at Department of Energy (DOE)’s Leadership Computing Facilities. Additionally, this research will provide opportunities to collaborate with experimentalists at the Linac Coherent Light Source facility and guide their experiments to produce new datasets useful to machine learning applications.
What You Need
Minimum Job Requirements:
A Ph.D. in a STEM discipline earned within the last 5 years. (Applicants may apply before graduation.)
Demonstrated expertise in one of the following:1. High-performance computing (HPC) code development and workflow2. Parallel programming such as Message Passing Interface (MPI), OpenMP or threading libraries, and/or GPU programming3. Applications or methods development in machine learning for atomistic systems
Strong programming experience, preferably in Python/PyTorch, C/C++, and/or GPU languages (e. g. CUDA).
Proficiency in common software engineering practices for scientific computing such as version control, continuous integration and unit testing.
Basic proficiency with artificial neural networks for machine learning.
Demonstrated experience in conducting original scientific research through peer reviewed publication record.
Excellent communication skills (both oral and written).
Experience with task-based HPC workflows for parallel scientific computation (e.g. Flux resource management, Dask, or Parsl in Python).
Experience with neural networks for atomistic potentials and/or physics-informed machine learning.
Experience with enhanced sampling or nonequilibrium simulation techniques (classical, semi-empirical, or quantum mechanical).
Demonstrated ability to work independently.
Interest and flexibility to adapt to new areas of research.
Ability to work effectively as a part of a team in a multi-disciplinary environment and interact with people with a variety of expertise.
Education: A Ph.D. in Computational or Computer Science, Machine Learning, Physics, Chemistry, Materials Science, or a related field, completed within the last five years or soon to be completed.
Dr. Ying-Wai Li ( firstname.lastname@example.org ) andDr. Nicholas Lubbers ( email@example.com )
Position does not require a security clearance. Selected candidates will be subject to drug testing and other pre-employment background checks.
New-Employment Drug Test: The Laboratory requires successful applicants to complete a new-employment drug test and maintains a substance abuse policy that includes random drug testing.
Candidates may be considered for a Director's Postdoc Fellowship and outstanding candidates may be considered for the prestigious Richard P. Feynman, Darleane Christian Hoffman, J. Robert Oppenheimer, or Frederick Reines Distinguished Postdoc Fellowships.
For more information about the Postdoc Program, go to https://www.lanl.gov/careers/career-options/postdoctoral-research/index.php .
Equal Opportunity: Los Alamos National Laboratory is an equal opportunity employer and supports a diverse and inclusive workforce. All employment practices are based on qualification and merit, without regard to race, color, national origin, ancestry, religion, age, sex, gender identity, sexual orientation or preference, marital status or spousal affiliation, physical or mental disability, medical conditions, pregnancy, status as a protected veteran, genetic information, or citizenship within the limits imposed by federal laws and regulations. The Laboratory is also committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations, upon request, for individuals to participate in the application and hiring process. To request such an accommodation, please send an email to firstname.lastname@example.org or call 1-505-665-4444 option 1.
Where You Will Work
Located in beautiful northern New Mexico, Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in strategic science on behalf of national security. Our generous benefits package includes:
§ PPO or High Deductible medical insurance with the same large nationwide network
§ Dental and vision insurance
§ Free basic life and disability insurance
§ Paid maternity and parental leave
§ Award-winning 401(k) (6% matching plus 3.5% annually)
§ Learning opportunities and tuition assistance
§ Flexible schedules and time off (paid sick, vacation, and holidays)
§ Onsite gyms and wellness programs
§ Extensive relocation packages (outside a 50 mile radius)
Vacancy Name: IRC81480
Organization Name CCS-7/Applied Computer Science
Req ID: IRC81480