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We are seeking a Postdoctoral Fellowship in Computational Astrophysics of Star Formation to join the Design Physics Division within Lawrence Livermore National Laboratory.
The postdoctoral fellow will conduct research in a broad research program in star formation studies using a state-of-the-art adaptive mesh refinement (AMR) radiation MHD code. The research program will focus on multiscale, multiphysics simulations of the formation of super star clusters and Orion-scale clusters under the influence of stellar feedback. The postdoctoral fellow will also conduct research on the formation of individual stars, both low mass and high mass.
The opportunity can begin September 2020 or earlier and is a two-year appointment with the possibility of extending to a maximum of three years. The successful candidate will hold a PhD in astronomy, astrophysics or physics and must have experience in computational astrophysical fluid dynamics, preferably including MHD and radiation transfer. Experience in computational star formation is desirable.
- Conduct research in a broad research program in star formation studies using a state-of-the-art adaptive mesh refinement (AMR) radiation MHD code
- Conduct research on the formation of individual stars, both low mass and high mass.
- Interact with a broad spectrum of scientists both internally and externally to the Laboratory.
- Publish research results in peer-reviewed scientific or technical journals, and present results at external conferences, seminars and/or technical meetings.
- The program will focus on multiscale, multiphysics simulations of the formation of super star clusters and Orion-scale clusters under the influence of stellar feedback.
- Perform other duties as assigned.
- Recent PhD in astronomy, astrophysics, or physics.
- Experience in high-quality research in a relevant field.
- Demonstrated significant accomplishments in numerical simulations and modeling and/or the application of theoretical techniques.
- Experience developing innovative solutions to scientific and technical problems.
- Demonstrated proficient verbal and written communication and interpersonal skills to collaborate effectively in a multidisciplinary team environment and present and explain technical information.
- Experience in computational star formation.
Pre-Employment Drug Test: External applicant(s) selected for this position will be required to pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.
Security Clearance: This position requires a Department of Energy (DOE) Q-level clearance.
If you are selected, we will initiate a Federal background investigation to determine if you meet eligibility requirements for access to classified information or matter. In addition, all L or Q cleared employees are subject to random drug testing. Q-level clearance requires U.S. citizenship. If you hold multiple citizenships (U.S. and another country), you may be required to renounce your non-U.S. citizenship before a DOE L or Q clearance will be processed/granted.
Note: This is a 2 year Postdoctoral appointment with the possibility of extension to a maximum of 3 years. Eligible candidates are recent PhDs within five years of the month of the degree award at time of hire date.
Lawrence Livermore National Laboratory (LLNL), located in the San Francisco Bay Area (East Bay), is a premier applied science laboratory that is part of the National Nuclear Security Administration (NNSA) within the Department of Energy (DOE). LLNL's mission is strengthening national security by developing and applying cutting-edge science, technology, and engineering that respond with vision, quality, integrity, and technical excellence to scientific issues of national importance. The Laboratory has a current annual budget of about $2.3 billion, employing approximately 6,900 employees.
LLNL is an affirmative action/ equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, protected veteran status, age, citizenship, or any other characteristic protected by law.