Graduate Research Associate

Los Alamos National Laboratory

Los Alamos, NM

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JOB DETAILS

SKILLS

Academic Research, Algorithms, Analysis Skills, Applied Physics, Artificial Intelligence (AI), Bayesian Networks, C++ Programming Language, Chemical Processes, Chemistry, Communication Skills, Computer Engineering, Computer Programming, Customer Support/Service, Data Modeling, Data Quality, Data Sets, Establish Priorities, Experiment Design, Instrumentation, Insurance, Laboratory, MATLAB, Machine Learning, Manufacturing, Material Science, Materials Engineering, Microsoft Visual Basic, Open Source, Operations Security (OPSEC), Powder Metallurgy, Presentation/Verbal Skills, Problem Solving Skills, Process Development, Programming Languages, Publications, Python Programming/Scripting Language, Quality Metrics, Safety/Work Safety, Science Software, Statistics, Team Player, Tuition Fees, Writing Skills

LOCATION

Los Alamos, NM

POSTED

30+ days ago

What You Will Do

Staff in the Materials Science in Radiation and Dynamics Extremes Group (MST-8) in the Materials Science and Technology Division at Los Alamos National Laboratory (LANL) are seeking a candidate for the Graduate Research Assistant Program in computational materials science and data-driven experimental design. The position is in support of several research projects that address multi-scale problems relating to nuclear fuel systems, including oxide, metallic, and other non-oxide ceramics fuels as well as steel, zirconium, and silicon carbide cladding, as well as their performance in reactor systems. This position supports academic research focused on the development of advanced computational methods for adaptive experimental design in quantitative elemental imaging workflows. The research will involve the design, implementation, and evaluation of advanced computational algorithms

Identify spatial and compositional patterns in multi-element mapping datasets (e.g., gradients, segregation, inclusions, clustering, interfaces, and anomalous regions);
Recommend follow-on measurement actions to maximize information gain, including:

Identifying regions where additional raster scans should be performed,
Suggesting locations for higher-resolution or higher-statistics scans,
Proposing targeted point analyses to refine compositional estimates.
Optimize acquisition parameters (e.g., dwell time, step size, spatial resolution, and count-statistics proxies) to enhance data quality while respecting operational and instrument constraints.
Detect and manage out-of-bounds or invalid parameter selections by incorporating safe operating limits into the decision-making framework.
Integrate uncertainty quantification and data-quality metrics to prioritize measurements and avoid low-value or unreliable regions.

The student will implement the developed methods in Python-based, open-source software with emphasis on reproducibility, modular architecture, and transparency. The resulting codebase will be structured as a generalizable, community-accessible framework suitable for peer-reviewed publication and broad dissemination.

The ideal candidate will be pursuing the above topic for their own research in their university.

What You Need

Minimum Job Requirements:

Successfully complete a minimum of 6 graduate credit hours per semester (or the equivalent of full-time enrollment). All students MUST remain enrolled at their university while working at the Lab during the academic year.
Have and maintain a minimum cumulative GPA of 3.2 on 4.0 scale.
Pass a 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.
Fluency in one or more computer programming languages (e.g., Matlab, Python, Visual Basic, C++, etc.)
Strong communication skills, both orally and in writing, for a wide range of audiences.

Education/Experience:

Currently Enrolled in a master's program in materials science, applied physics, computer engineering, or a closely related discipline.

Desired Qualifications:

Strong programming experience in Python, including scientific computing libraries (NumPy, SciPy, scikit-learn, PyTorch/TensorFlow, etc.);
Experience with machine learning, AI methods, or data-driven modeling.
Familiarity with uncertainty quantification, statistical inference, or Bayesian experimental design.
Experience analyzing spatially resolved or imaging datasets.
Demonstrated ability to design and implement modular, reproducible scientific software.
Experience working with scientific instrumentation data or experimental workflows (preferred).
Demonstrated ability to conduct independent and collaborative research.
Strong written and oral communication skills.

Work Location: The work location for this position is onsite and located in Los Alamos, NM. All work locations are at the discretion of management.

Note to Applicants:

The cover letter should address the relevant job requirements and skills desired of this position, with specific examples from your academic and research experience. Expected degree completion dates and relevant coursework should also be included.
Evaluation of applications will commence immediately and continue until the position is filled.

Requirements for acceptance:

No Clearance Required: Position does not require a security clearance. Selected candidates will be subject to drug testing and other pre-employment background checks.

Due to federal restrictions contained in the current National Defense Authorization Act, citizens of the People's Republic of China-including the special administrative regions of Hong Kong and Macau-as well as citizens of the Islamic Republic of Iran, the Democratic People's Republic of Korea (North Korea), and the Russian Federation, who are not Lawful Permanent Residents ("green card" holders) are prohibited from accessing facilities that support the mission, functions, and operations of national security laboratories and nuclear weapons production facilities, which includes Los Alamos National Laboratory.
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.

The Sigma Manufacturing Science Division focuses on materials science, engineering, and chemistry, emphasizing metallurgical, powder, and chemical processes and research. Our mission is to provide outstanding manufacturing science and engineering solutions to support our national security and industry customers-a scope that spans metallic, ceramic, and organic materials composed of elements ranging from hydrogen to uranium on the periodic table, with a strong emphasis on unconventional and low-symmetry materials. We are a flexible, integrated one-stop shop providing exceptional customer service from concept and process development to fabricated finished products.

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 childbirth and parental leave
Award-winning 401(k) (6% matching plus 3.5% annually)
Learning opportunities and tuition assistance
Flexible schedules and time off (PTO and holidays)
Onsite gyms and wellness programs
Extensive relocation packages (outside a 50 mile radius)

Additional Details

Directive 206.2 - Employment with Triad requires a favorable decision by NNSA indicating employee is suitable under NNSA Supplemental Directive 206.2. Please note that this requirement applies only to citizens of the United States. Foreign nationals are subject to a similar requirement under DOE Order 142.3A.

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. Although New Mexico and other states have legalized the use of marijuana, use and possession of marijuana remain illegal under federal law. A positive drug test for marijuana will result in termination of employment, even if the use was pre-offer.

Internal Applicants: Regular appointment employees who have served the required period of continuous service in their current position are eligible to apply for posted jobs throughout the Laboratory. If an employee has not served the required period of continuous service, they may only apply for Laboratory jobs with the documented approval of their Division Leader. Please refer to Policy Policy P701 for applicant eligibility requirements.

Equal Opportunity: Los Alamos National Laboratory is an equal opportunity employer. All employment practices are based on qualification and merit, without regard to protected categories such as race, color, national origin, ancestry, religion, age, sex, gender identity, sexual orientation, 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, state, and local 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 (505)-664-6947.

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Select the Click Here button if you have been employed with the Lab or received insurance coverage.
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About the Company

Los Alamos National Laboratory

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