DEVCOM Army Research Laboratory
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Computational Materials Science Research - Multi-Scale Modeling DEVCOM Army Research Laboratory in United States
Degree Level
Master's, Postdoc
Field of study
Computer Science
Funding
Available
Country
United States
University
DEVCOM Army Research Laboratory
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Keywords
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About this position
This research opportunity at the DEVCOM Army Research Laboratory focuses on computational materials science for multi-scale and multi-physics modeling. The project is aimed at accelerating materials development by creating high-fidelity computational models that can connect physical behavior across multiple scales and support analysis, optimization, and design.
The advertised research emphasizes the development of computational methodologies, especially numerical methods and associated algorithms, that can help build new multi-scale materials models able to run efficiently on modern extreme-scale computing environments. A major challenge highlighted in the posting is how to bridge different length and time scales while keeping models usable in practice.
Another central theme is surrogate modeling. The opportunity calls for new adaptive, non-local surrogate modeling approaches that can reduce the cost of expensive at-scale simulations without losing the fidelity needed for real materials design applications. The research also addresses uncertainty in at-scale models, including variability from natural fluctuations, model parameters, and model form, and the need to incorporate that uncertainty consistently into multi-scale simulations.
The work is situated within the Network Cyber & Computational Sciences area and the broader research environment of the Army Research Laboratory. The posting also places the opportunity within ARL’s wider mission to advance science and technology in areas including materials science, mathematics, physics, and computational sciences. Three ARL advisors are named for the opportunity: Jaroslaw Knap, Joshua Crone, and Benjamin MacCall.
The research is relevant to computational design of materials and to the development of scalable simulation tools for high-performance computing environments.
Funding details
Available
What's required
U.S. citizen only. Applicants may hold an associate’s, bachelor’s, master’s, or doctoral degree, with listed academic levels including journeyman fellow, senior fellow, postdoctoral fellow, or faculty status. Discipline preferences include chemistry and materials sciences, computer, information, and data sciences, engineering, mathematics and statistics, and physics. A complete application requires a CV or resume, three reference forms, and transcripts showing degree receipt; if selected, the applicant must also prepare a research proposal related to a specific ARL opportunity.
How to apply
Apply through the Zintellect opportunity page. Upload a CV or resume, provide three references, and submit transcripts with proof of degree completion. If selected by an advisor, prepare and upload the required research proposal when the link is provided.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.