What You Will Do

We are looking for candidates to join our team in Los Alamos National Laboratory's Theoretical Division (T-Division). T-Division provides a unique and engaging environment that fosters multi-disciplinary collaborations to support the laboratory's strategic basic research and national security missions. The Applied Mathematics and Plasma Physics (T-5) group within T-Division conducts diverse research across a variety of topics including fusion science, space plasma science, astrophysics, numerical analysis, machine learning, computational imaging, optimization, artificial intelligence, environmental sciences, and the modeling of critical infrastructure (gas pipelines and electrical grids). These application areas are tied together by research in novel algorithms and numerical methods.

This position is part of LANL's Advanced Network Science Initiative (ANSI) team. ANSI performs basic and applied research focused on modeling and understanding the nation's critical infrastructures, such as electric power and natural gas. Our expertise covers statistics, stochastic methods, machine learning, control theory, dynamical systems, discrete and continuous optimization, statistical physics, and graphical modeling. We ensure the scientific and technological validity of our approaches by working closely with physicists, engineers, mathematicians, statisticians, computer scientists, and economists through interdisciplinary collaborations. Our typical customers include DHS, DOE, DOD, and other national laboratories. Our research requires close collaborations within and outside the Laboratory. More details on ANSI can be found at https://lanl-ansi.github.io/

Candidates are expected to support programs within the U.S. Department of Energy's Office of Electricity, Office of Science, ARPA-E, and similar sponsors. Programs and projects include control and optimization of networks under uncertainty, analysis of extreme events, design of resilient networks, modeling of interdependent networks, machine learning for infrastructure systems, and fundamentals of optimization, machine learning, and quantum computing methods. Selected candidates will work with the team to conduct novel research in the areas listed above, will publish the results in peer-reviewed journals, and will present at conferences and workshops. They will also be developing their own R&D portfolio within the larger team. The candidates will participate in the development of proposals to internal and external organizations to fund the teams research activities. The candidate is expected to work in an interdisciplinary environment with substantial collaborative research. This includes collaborating with scientists and managers to develop and sustain programs as well as recruiting, mentoring, and supporting students and postdocs. They will be expected to foster an inclusive environment at the workplace.

What You Need

Minimum Job Requirements:

• Expertise in one or more of the following areas: artificial intelligence, machine learning, optimization, control theory, data science, computational science, applied mathematics, or quantum information science.

• Ability to work effectively in a collaborative environment.

• Technical oral and written skills as demonstrated through publications and conference presentations.

Education/Experience: Position requires a Bachelor' degree in a STEM field from an accredited college and university and 4 years of related experience, typically with post-doctoral research experience at a university or national lab or equivalent experience directly related to the occupation.

Desired Qualifications:

• Experience in proposal development.

• Programming experience with C++, Java, Julia, MATLAB, or Python.

• Experience with artificial intelligence or machine learning.

• Optimization modeling experience with AMPL, GAMS, JuMP, or Pyomo.

• Experience with open-source software and commercial solvers (CPLEX, Gurobi, IPO, pT, PyTorch, Tensorflow, etc.).

• Experience with mentoring students or postdocs.

• Ability to obtain a DOE Q Clearance.

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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.

Position commitment: Regular appointment employees are required to serve a period of continuous service in their current position in order to be eligible to apply for posted jobs throughout the Laboratory. If an employee has not served the time required, they may only apply for Laboratory jobs with the documented approval of their Division Leader. The position commitment for this position is 1 year.

Note to Applicants:

• Include a detailed cover letter with the application that addresses how you meet the required qualifications and any desired qualifications.

• This position is open to citizens of all nationalities.

• Contact t5jobs@lanl.gov for any questions about the position or additional details.

• For full consideration please apply by March 18th, 2024

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 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 (https://directives.nnsa.doe.gov/supplemental-directive/sd-0206-0002) . 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.

Regular position: Term status Laboratory employees applying for regular-status positions are converted to regular status.

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 (https://int.lanl.gov/policy/documents/P701.pdf) for applicant eligibility requirements.

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, 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.