Sort by
Refine Your Search
-
include the design and implementation of finite element multiscale models and machine learning algorithms, analyzing related experimental data, and collaborating with industrial collaborators to validate
-
(variational multiscale, multiscale finite elements, etc.), structure preserving numerical methods, stochastic optimization, analysis of machine learning methodologies, multilevel methods, scale-bridging and
-
methods (e.g., AFM, Nano-IR, STM, SECCM, SICM, SECM), advanced light and electron microscopy, materials synthesis (e.g., conductive metal-organic frameworks, 2D/hierarchical structures, nanoparticles
-
the valuation of natural assets? This interdisciplinary research builds on real options theory and modern computational methods to assess dynamic, irreversible decisions under uncertainty. By blending tools from
-
. Extensive experience in the development and application of finite element method (FEM) or comparable methods for AM applications. Preferred Qualifications: Demonstrated expertise in multi-physics simulations
-
Postdoctoral Researcher position in AI and machine learning, with a focus on patient-specific reconstruction of coronary vessels and the simulation of stenting techniques using Finite Element Analysis (FEA) and
-
part of a degree program. In particular, knowledge about finite-element analysis is an absolute must . Familiarity with iterative solvers , preconditioners , multigrid methods , and mixed-precision
-
., Multiphysics finite element analysis, Matlab, Labview etc.) cleanroom experience, and characterization of electronic devices are required. Further, knowledge of system level integration and haptics feedback in