Looking for an opportunity to make an impact?
We are seeking a Computational Materials Scientist interested in joining a distributed, multidisciplinary team working on the cutting edge of high-performance computing (HPC) and structural materials development. This work specifically supports accelerating the design and development of cost-effective high-performance alloys for extreme environments (such as high temperature, high stress, water vapor, hydrogen, oxidation, corrosion, etc.) using multiscale computational modeling and machine learning. The overarching goal is to address potential consequences of shifting from natural gas to hydrogen on the environmental degradation of post-combustion metallic components in power generation turbines. Efforts in this task will further lay the groundwork for the design of cost-effective materials broadly focused on enabling DOE efficiency and emissions targets.
Come join the Leidos Research Support Team supporting the National Energy Technology Laboratory (NETL), where you’ll be able to work side by side conducting research with world-class scientists and engineers using state of the art equipment to contribute to new areas of basic and applied research; discover, integrate, and mature technology solutions to enhance the nation’s energy foundation and protect the environment for future generations. You will contribute to the development of patents, written reports, journal articles, and contribute to presentations on findings, highlights, and innovative solutions in DOE-sanctioned meetings, scientific conferences, and national committees. Explore the Research Support Services (RSS) contract for the U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) here - https://netl.doe.gov/
- Develop a reliable framework for predicting alloy oxidation performance and designing oxidation-resistant alloys using a combination of high throughput DFT (VASP) and CALPHAD (using TC Python).
- Collect, curate, and analyze literature data pertaining to oxidation behavior of alloys and scale spallation at high temperatures.
- Predict thermodynamics, kinetics, and phase transformations of alloys pertaining to oxidation behavior using CALPHAD, density functional theory methods, and other approaches.
- Predict composition-processing-microstructure-oxidation relationship using machine learning models and recommend new alloys with enhanced properties.
Required Education & Experience:
- Ph.D. degree in Materials Science, Chemical or Mechanical Engineering, or a related field with 1+ years experience.
- Solid knowledge in CALPHAD methodology and databases. Demonstrated hands-on skills in CALPHAD modeling in phase diagrams, diffusion, and phase transformations using ThermoCalc, Dictra, and Prisma.
- Excellent computer programming and coding skills such as Python, C/C++, Fortran, Linux script, parallel computing, etc. Demonstrated proficiency in supercomputers and Linux system.
- Research experience in first principles density functional theory (DFT) calculations to predict thermodynamic, kinetic, and mechanical properties using VASP package.
- Must be able to meet the requirements for gaining access to work on the NETL campus.
- Research experience in environmental degradation such as oxidation of alloys.
- Research experience in molecular dynamics simulations such as LAMMPS, finite element methods, and/or crystal plasticity.
- Excellent record of peer-reviewed quality publications.
- Excellent oral and written communication skills.
- Ability to work independently and with minimum supervision.
- Ability to work effectively as a part of a team in a multi-disciplinary environment and interact with people with a variety of expertise.
- Machine learning a plus.
Salary Range for this position: $95K to $110K
Pay Range:Pay Range $78,000.00 - $120,000.00 - $162,000.00
The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
Leidos is a Fortune 500® technology, engineering, and science solutions and services leader working to solve the world’s toughest challenges in the defense, intelligence, civil, and health markets. The company’s 45,000 employees support vital missions for government and commercial customers. Headquartered in Reston, Virginia, Leidos reported annual revenues of approximately $14.4 billion for the fiscal year ended December 30, 2022. For more information, visit www.Leidos.com.
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All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos will also consider for employment qualified applicants with criminal histories consistent with relevant laws.