What You Will Do
The successful candidate is to join our Computational Earth Science Group; however, the work involves collaborations from other LANL groups and divisions. She/he will work on developing and applying novel methods and computational techniques for large dataset analyses based on machine learning methods. The work will be building on already existing software (e.g., MADS, mads.lanl.gov, and CHROTRAN, chtrotran.lanl.gov). The research is expected to produce a series of peer-reviewed publications in high-impact journals. The term of the appointment is 1 to 2 years; depending on the performance and funding availability there are opportunities to extent the appointment by transitioning to other types of LANL positions.
What You Need
- Minimum Job Requirements:
- Strong applied math and computational science skills
- Code development and computational experience in using high-performance parallel computing resources
- Experience in data- or model-based analyses involving large datasets
- Excellent communication, writing and oral presentation skills, and
- Fluency in one or more programming languages including high-level dynamic languages
Desired Skills:
- Model calibration and uncertainty quantification
- Large dataset analyses
- Application and development of machine learning methods
- Demonstrated record of peer-reviewed publications
- Quantum computing interests or experience
- Theoretical understanding of processes related to fluid flow and contaminant transport in geologic media
- Experience in analysis and application of numerical models of flow and contaminant transport in geologic media
Education:
A M.Sc. in Applied Math, Statistics, Computational Sciences, Physics, Hydrology, Hydrogeology, or Engineering completed within the last three years and have not yet been accepted into another master’s program or Ph.D. program.
Notes to Applicants:
For further information, check out New Hire. LANL offers an excellent working environment and competitive compensation and benefits package. Additional information about this position and the Subsurface Flow and Transport team can be obtained by contacting Velimir V Vesselinov (vvv@lanl.gov, +1 505 665-1458), and Daniel O’Malley (omalled@lanl.gov, +1 505 667-8684).
Additional Details:
No Clearance: 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.
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 regards 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 applyhelp@lanl.gov or call 1-505-665-4444 option 1.
For general program information refer to the Student Programs web page.
Where You Will Work
The Computational Earth Science Group (EES-16) in the Earth and Environmental Sciences (EES) Division at Los Alamos National Laboratory (LANL) has an immediate opening for a creative and resourceful postmasters candidate with strong applied math and computational science skills.
EES employs about 110 scientists and 40 postdocs as well as many students, with expertise in various facets of Earth science. The successful candidate will join the dynamic and interdisciplinary Subsurface Flow and Transport (SFT) Team that includes more than 20 researchers working on projects related to strategic national-interest problems dealing with energy and environmental security. SFT works towards development of strategic scientific capabilities to address challenging issues related to environmental problems, energy and water production, carbon capture and sequestration, and waste disposition and storage. Many of LANL projects address the nation’s most challenging environmental and Earth science problems. Our research includes active collaborations with universities and other national laboratories. The projects also include extensive research work related to high-performance computing. The successful candidate will interact with researchers and application-oriented scientists on this team as well as in other Earth sciences, computing, and physics groups. Access will be provided to advanced numerical simulation codes and state-of-the-art computing facilities within EES and at LANL.
Located in northern New Mexico, Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in strategic science on behalf of national security. LANL enhances national security by ensuring the safety and reliability of the U.S. nuclear stockpile, developing technologies to reduce threats from weapons of mass destruction, and solving problems related to energy, environment, infrastructure, health, and global security concerns.
Contact Name: Gasca, Alicia M
Organization Name: EES-16/Computational Earth Science
Email: agasca@lanl.gov
Job Title: Applied Computational Post-Master’s Student
Appointment Type: GRA
Req ID: IRC59852