Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
developing finite element simulation libraries with comprehensive documentation and user-friendly interfaces Experience in software integration of advanced numerical solvers and imaging and simulation tools
-
modeling and simulation (e.g., finite element analysis, discrete event simulation). Experience with Infrastructure as Code tools (e.g., Terraform, Ansible). Experience with HPC clusters and workload
-
fundamentals Technical writing Data analysis MATLAB, Excel, PowerPoint, CAD Preferred skills/experience areas include: Finite element analysis Experimental test conduct Acoustics Dimensional tolerance stack-up
-
for: The development of multi-scale models of polyelectrolyte gels using asymptotic methods. Numerically solving the models using, for example, the finite element method. Collaborating with experimental researchers
-
fundamental, and expert knowledge of CAD and finite element design is absolutely needed (preferably Creo Parametric and Ansys). A strong understanding of accelerator systems or similar complex, large-scale
-
high computational cost presents a challenge for real-time process control. This project aims to overcome this limitation by integrating real-world casting data, process parameters, and finite element
-
emerging fields. Courses will leverage expertise with computer-aided design, engineering and prototyping, Finite Element Analysis (FEA), and applications of AI and machine learning. Encouraged to develop and
-
to improve the accuracy of discontinuous Galerkin (DG) finite element methods. Recent work by our collaborator at the University of Tennessee has shown that optimal placement of high-order nodes can
-
uneven surfaces. Lifting, climbing ladders, squatting, twisting, using sprayers, walking on a variety of surfaces, digging, planting and exposure to the elements is commonplace. This role requires highly
-
to improve the accuracy of discontinuous Galerkin (DG) finite element methods. Recent work by our collaborator at the University of Tennessee has shown that optimal placement of high-order nodes can