Los Alamos National Security LLC
Physics Visualization and Analysis Post-Masters (Post-masters student)
Los Alamos National Security LLC, Los Alamos, New Mexico, us, 87545
What You Will Do
Are you ready to begin a career in verification, validation, uncertainty quantification (VVUQ), and machine learning? If so, we encourage you to learn more about our student openings in the Computational Physics: Verification & Analysis group (XCP-8) at Los Alamos National Laboratory (LANL). Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in science and engineering on behalf of national security. You will work with the Computational Physics: Verification & Analysis group (XCP-8) on developing visualization and analysis workflows for large-scale simulation data using Ensight and/or ParaView. A background in physics or engineering (e.g., nuclear, hydrodynamics, fluid dynamics, shock physics, turbulence, solid mechanics, material strength, plasma physics, radiation transport, magnetohydrodynamics) is preferred. A self-motivated, creative researcher will find this environment conducive to growth. As a post-master's student, you will receive mentoring from an expert team. What You Need
Minimum Job Requirements:
Computational Physics and High Performance Computing: Experience with computational physics simulations on HPC architectures, e.g., CFD, hydrodynamics, finite element analysis. Physics Visualization: Experience with visualization tools like ParaView, VisIt, or Ensight for large-scale simulation data. Research Expertise: Conducted research in areas such as fluid dynamics, solid mechanics, materials, equation of state, high explosives, high-energy-density physics, radiation transport, validation, uncertainty quantification, machine learning, or related fields. Programming: Strong skills in Fortran, C++, or Python; experience with Matlab or R may be substituted. Learning Agility and Communication: Ability to rapidly learn new skills and communicate effectively in a diverse, interdisciplinary team environment, demonstrated through publications or conference presentations. Education/Experience:
Masters in mathematics, physics, computer science, engineering, or related field. Candidates must be within 3 years of completing their bachelor's degree or have completed all requirements by the appointment start date. Candidates should not be enrolled in another graduate program at that time. Q-Clearance:
Ability to obtain a Q-clearance (generally requires U.S. citizenship and no recent illegal drug use). Desired Qualifications:
Proficiency with Python and VTK Experience with Ensight, Paraview, or similar visualization software Experience working with computational physics datasets Knowledge of modern software development tools (Git, Docker, SQL, etc.) Experience with classified computing systems Work Environment
Location: Onsite in Los Alamos, NM. All decisions regarding work location are at management discretion. Note to Applicants
Applicants must be U.S. citizens and able to obtain a Q-clearance. Due to federal restrictions, citizens of certain countries are prohibited from accessing LANL facilities. Applicants should submit a CV and a detailed cover letter explaining their relevant experience. For questions, contact Dr. Brandon Wilson at bwilson@lanl.gov. Where You Will Work
Located in northern New Mexico, LANL offers benefits including health insurance, 401(k), tuition assistance, flexible schedules, onsite gyms, and relocation packages. Additional Details
This position requires a Q clearance and is subject to background checks, drug testing, and other federal employment requirements. Equal opportunity employment is committed to diversity and inclusion. For accommodations during the application process, contact applyhelp@lanl.gov. How to Apply
Applicants with prior employment or insurance coverage at LANL should activate their existing account with their name and email, then enter the validation code from email within 15 days. New applicants should register to create a new account. To apply, log in, view job details, and submit your application or save it for later. For technical assistance, email applyhelp@lanl.gov.
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Are you ready to begin a career in verification, validation, uncertainty quantification (VVUQ), and machine learning? If so, we encourage you to learn more about our student openings in the Computational Physics: Verification & Analysis group (XCP-8) at Los Alamos National Laboratory (LANL). Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in science and engineering on behalf of national security. You will work with the Computational Physics: Verification & Analysis group (XCP-8) on developing visualization and analysis workflows for large-scale simulation data using Ensight and/or ParaView. A background in physics or engineering (e.g., nuclear, hydrodynamics, fluid dynamics, shock physics, turbulence, solid mechanics, material strength, plasma physics, radiation transport, magnetohydrodynamics) is preferred. A self-motivated, creative researcher will find this environment conducive to growth. As a post-master's student, you will receive mentoring from an expert team. What You Need
Minimum Job Requirements:
Computational Physics and High Performance Computing: Experience with computational physics simulations on HPC architectures, e.g., CFD, hydrodynamics, finite element analysis. Physics Visualization: Experience with visualization tools like ParaView, VisIt, or Ensight for large-scale simulation data. Research Expertise: Conducted research in areas such as fluid dynamics, solid mechanics, materials, equation of state, high explosives, high-energy-density physics, radiation transport, validation, uncertainty quantification, machine learning, or related fields. Programming: Strong skills in Fortran, C++, or Python; experience with Matlab or R may be substituted. Learning Agility and Communication: Ability to rapidly learn new skills and communicate effectively in a diverse, interdisciplinary team environment, demonstrated through publications or conference presentations. Education/Experience:
Masters in mathematics, physics, computer science, engineering, or related field. Candidates must be within 3 years of completing their bachelor's degree or have completed all requirements by the appointment start date. Candidates should not be enrolled in another graduate program at that time. Q-Clearance:
Ability to obtain a Q-clearance (generally requires U.S. citizenship and no recent illegal drug use). Desired Qualifications:
Proficiency with Python and VTK Experience with Ensight, Paraview, or similar visualization software Experience working with computational physics datasets Knowledge of modern software development tools (Git, Docker, SQL, etc.) Experience with classified computing systems Work Environment
Location: Onsite in Los Alamos, NM. All decisions regarding work location are at management discretion. Note to Applicants
Applicants must be U.S. citizens and able to obtain a Q-clearance. Due to federal restrictions, citizens of certain countries are prohibited from accessing LANL facilities. Applicants should submit a CV and a detailed cover letter explaining their relevant experience. For questions, contact Dr. Brandon Wilson at bwilson@lanl.gov. Where You Will Work
Located in northern New Mexico, LANL offers benefits including health insurance, 401(k), tuition assistance, flexible schedules, onsite gyms, and relocation packages. Additional Details
This position requires a Q clearance and is subject to background checks, drug testing, and other federal employment requirements. Equal opportunity employment is committed to diversity and inclusion. For accommodations during the application process, contact applyhelp@lanl.gov. How to Apply
Applicants with prior employment or insurance coverage at LANL should activate their existing account with their name and email, then enter the validation code from email within 15 days. New applicants should register to create a new account. To apply, log in, view job details, and submit your application or save it for later. For technical assistance, email applyhelp@lanl.gov.
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