Los Alamos National Laboratory Computational Modeling Post-Bac Student in Los Alamos, New Mexico
What You Will Do
This is a 1-year post-baccalaureate position at Los Alamos National Laboratory’s (LANL) Computational Physics Division, with potential to extend to a second year. 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. The successful candidate will engage in developing probabilistic optimization methods related to uncertainty in model forms, developing uncertainty quantification methods for reduced order models using machine learning algorithms and propagating uncertainty through large-scale predictive physics-based simulations. 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. Experience with interpreted languages such as Python, Matlab, or R is required, Python experience being the most desirable.
What You Need
Minimum Job Requirements:
Completion of a Bachelors degree(s) in the science, engineering, mathematics and/or computing
Familiarity with optimization, uncertainty quantification or machine learning methods;
Strong programming skills in Fortran, C++ and/or Python. Alternately experience programming in Matlab may be substituted;
Strong verbal and written communication skills;
Eligibility limited to students who have completed a bachelor's degree within the past 3 years, but have not been accepted and enrolled in a graduate program.
Programming skills in Python, Matlab, IDL, R or other relevant software language and the ability to adopt and apply new software packages and approaches for spatial data analysis;
Experience with modeling/implementing physics models in LANL codes
Familiarity with Machine Learning packages such as TensorFlow and Scikit-learn
Familiarity with using High Performance Compute clusters
Experience with version-controlled code projects
Willing and able to work within LANL and sponsor prescribed ethics, ES&H, safety and security plans;
Support and/or lead the presentation and publication of research, including peer-reviewed papers;
Hardworking, flexible, organized, and a self-starter with a positive attitude;
Demonstrate ability to work with minimal supervision and as a team player;
Ability to obtain a Q clearance
Completion of a Bachelor’s degree in science, engineering, mathematics and/or computing within the past 3 years but have not been accepted and enrolled in a graduate program with a cumulative GPA of at least a 3.2.
Note to Applicants:
As part of the application process, please upload your transcripts, cover letter, and resume on your LANL online profile.
Clearance: Q (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. SeeDOE Order 472.2for 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.
For general program information refer to theStudentProgramsweb page.
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 email@example.com 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
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Follow the instructions below if you have ever had an employee Z number, been a contractor, or received Los Alamos Lab insurance coverage to activate your account:
Select the Click Here button if you have been employed with the Lab or received insurance coverage .
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Enter your validation code as described in the email you receive and complete the 3-page registration form. Your account is now active and you can apply for jobs or save to your basket. Important : Enter the validation code within 15 days to activate your account or your account will be deactivated.
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Select the Register button if you have never been employed with the Lab or received insurance coverage to Create an Account.
From here, you will establish an account with username and password.
How to Apply: Login to Your Account to Complete the Application Process
Click the Vacancy Name number (in blue) to view any job’s details.
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If you experience any technical issues, please email firstname.lastname@example.org for assistance.
Contact Name Greenhall, Ashley Nelsen
Vacancy Name: IRC82341
Organization Name XCP-8/Verification And Analysis
Req ID: IRC82341
Category: Student - Post Bachelor