Los Alamos National Laboratory Jobs

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Job Information

Los Alamos National Laboratory Post Masters ST in Los Alamos, New Mexico

What You Will Do

The Information Systems and Modeling Group (A-1) is seeking a Post-Master’s students to join one of our dynamic teams! Multiple teams within the Information Systems and Modeling Group (A-1) are seeking team-oriented and highly-motivated students with a Master’s Degree. The selected students will partner with an experienced mentor who will provide guidance and feedback throughout the course of the internship.

The Information Systems and Modeling Group (A-1) is currently seeking Post Master students to join one of the following teams:

  • QUIC CBR Plume Modeling Team

  • Infrastructure Team

  • Data Analytics Team

What You Need

Minimum Job Requirements:

QUIC CBR Plume Modeling Team:

  • Educational background in Mechanical Engineering, Meteorology, Environmental Sciences, Chemical Engineering, Atmospheric Sciences, Nuclear Engineering, Civil Engineering, Aviation Sciences, or related technical field.

Data Analytics Team :

  • Educational background in Mathematics, Computer Science, Statistics, Public Health or related technical field.

Infrastructure Team :

  • Educational background in electrical engineering, chemical engineering, or related technical field.

  • Coursework is required in one or more of the following: electromechanical energy conversion, power systems, protection, smart grids, renewable energy, power electronics, electric machines and drives, electric vehicles.

  • Experience in power system modeling and simulation and familiarity with tools such as PowerWorld, MATPOWER, PSSE, PowerModels, Simscape, PSIM, or PSCAD.

  • Programming skills in MATLAB, Python, or Julia.

  • Relevant power engineering experience at electric utilities or through a senior design project is strongly preferred.

Communication : Good communication skills, brainstorming and writing skills are essential, as is working effectively as part of a team.

Programming Experience : Familiarity with Python, R, C++, MATLAB, or an equivalent programming language.

Desire to Learn : The desire to continually learn new things, as well as being open to working on a variety of topics.

Desired Qualifications:

QUIC CBR Plume Modeling Team:

  • Experience or strong interest in running numerical weather prediction, computational fluid dynamics, airborne plume transport and dispersion, and/or fire spread models

  • GPU coding experience

Data Analytics Team:

  • Experience processing social media data

  • Experience with large-scale data processing

  • Experience with high-performance computing and parallel computation

  • Experience with mathematical and/or statistical modeling

  • Experience with agent-based modeling

  • Experience with machine learning

  • Experience with natural language processing

  • Experience with geographic information system analysis

  • Experience analyzing and/or interpreting disease-related data

Education/Experience : Position requires a Master’s Degree in STEM (or a closely related field), with a minimum cumulative GPA of 3.2 on a 4.0 scale, or its equivalent within the last three years.

This position will be physically located in Los Alamos, NM.

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.

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.

426.2: This position is subject to DOE Order 426.2, Personnel Selection, Training, and Qualification Requirements for DOE Nuclear Facilities, which establishes entry-level requirements to ensure candidates selected for specific positions can successfully perform the requirements of the job.

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.

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 PolicyPolicy P701 for applicant eligibility requirements.

For general program information refer to the Student Programs web 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 applyhelp@lanl.gov or call 1-505-665-4444 option 1.

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Appointment Type

GRA

GRA

Contact Details
Contact Name Wilson, Amber
Email amberw@lanl.gov
Work Telephone
Vacancy Name: IRC89852
Organization Name Information Systems and Modeling Post-Master's Student
Minimum Salary
Maximum Salary
Req ID: IRC89852
Category: Student - Post Master

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