Los Alamos National Laboratory Uncertainty Quantification and Machine Learning Postdoc in Los Alamos, New Mexico
What You Will Do_
The Computational Physics: Verification & Analysis group (XCP-8) at the Los Alamos National Laboratory (LANL) has an opening for a postdoctoral research associate in the areas of uncertainty quantification and machine learning. The selected candidate will be part of a multi-disciplinary team as they assess the effect of experimental data on simulation uncertainty in large-scale physics simulations. This will involve collaborating with experimentalists and physics subject-matter experts in order to understand sources and types of uncertainties for a single physics sub-model or experimental setup. An immediate goal of the work will be to develop applications of machine learning classification methods to aid in determining the type of experimental data most needed to reduce simulation uncertainty. Though machine learning has showed promise in many fields, its use in predictive physics-based simulation is still very new. This is a promising growth area that can benefit from new ideas and unorthodox approaches.
Experience with interpreted languages such as Python, Matlab, or R is required, Python experience being the most desirable. The successful applicant should have a strong background in at least one of the specialty areas of continuous optimization, probabilistic optimization, uncertainty quantification, or machine learning methods.
A successful candidate will engage in one or more of the following focus areas:
Developing probabilistic optimization methods related to uncertainty in model parameterization
Development of machine learning algorithms to learn features in a wide variety of data sets that can be informed by experiment
Development of uncertainty quantification methods for reduced order models using machine learning algorithms
Development of methods to propagate uncertainty through large-scale predictive physics-based simulations
What You Need
Minimum Job Requirements:
Research-level expertise in optimization, uncertainty quantification, or machine learning, or a closely related focus area.
Demonstrated ability to communicate research to an interdisciplinary audience and work on an interdisciplinary team
Strong programming skills in Python. Alternately experience programming in Matlab or R may be substituted.
Familiarity with Unix
Demonstrated ability to publish research in peer-reviewed journals or conference proceedings
Familiarity with TensorFlow and Scikit-learn
Familiarity with using High Performance Compute clusters
Experience with version-controlled code projects
Education: Ph.D. in mathematics, physics, computer science, statistics, machine learning or a closely related discipline completed within the past five years or to be completed soon prior to employment.
Notes to Applicants: Applicants must submit a CV and include a cover letter describing their research interests. In addition to applying through the official site, please email your CV and cover letter directly to Kyle Hickmann (email@example.com).
Postdoctoral appointments are for two years, with the possibility of a third year extension.
Q Clearance(Position will be cleared to this level): Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements* for access to classified matter.
*Eligibility requirements: To obtain a clearance, an individual must be at least 18 years of age; U.S. citizenship is required except in very limited circumstances. See DOE Order 472.2 for additional information.
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 general information go to Postdoc Program.
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 firstname.lastname@example.org or call 1-505-665-4444 option 1.
Where You Will Work_
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.
Our diverse workforce enjoys a collegial work environment focused on creative problem solving, where everyone’s opinions and ideas are considered. We are committed to work-life balance and personal/professional growth. Our creative and dedicated computational professionals are our greatest asset and we take pride in cultivating their talents, supporting their efforts, and enabling their success. We encourage mentoring for new staff to build skills quickly and continued publications/research are prized as well. Together we are advancing our national security mission.
Compensation and Benefits;
Flexible work schedules
Exercise facility free for staff use
Choice of comprehensive medical plans
Paid maternal leave, sick time
401k match (100% up to 6% + kicker)
Fully vested in 401k day one
Los Alamos National Laboratory in Los Alamos, NM enjoys excellent weather, clean air and outstanding public schools. This is a safe, low-crime, family-oriented community with frequent concerts and events as well as quick travel to many top ski resorts, scenic hiking trails, and mountain climbing. The short drive to work includes stunning views of the Valles Caldera as well as the Sangre de Cristo mountains.
Location: Los Alamos, NM, US
Organization Name: XCP-8/Verification And Analysis
Job Title: Uncertainty Quantification and Machine Learning Postdoc
Appointment Type: Postdoc
Req ID: IRC66848