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someone with experience of running finite element models (FEM) of soft tissue mechanics. It is essential that the successful applicant can directly translate mathematical models to code (rather than
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of ABC-F proteins are often found within a genome, suggesting different functions for each paralog (Fostier et al., FEMS Letters 2021). Recently, we showed that the ABC-F protein EttA targeted
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heavy software development component. The successful candidate will perform research in the application of machine learning (ML) techniques to the finite element method (FEM) in the context of composites
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modeling of highly compact power electronic converter systems. Verification of the concepts using modern circuit simulators as well as FEM simulations. Construction of laboratory prototypes to verify
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to provide leadership in developing innovative solutions and sustainable technologies for space creation and urban infrastructure development. For more details, please view https://www.ntu.edu.sg/cus. We
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, natural language processing (NLP) and machine learning Connected and autonomous vehicles Disaster and natural Hazard assessment and management Discrete element method (DEM) and finite element methods (FEM
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experience with CAD/FEM software Experience in one or more of the following fields is a plus: simulation frameworks (e.g. SOFA, NVIDIA IsaacLab), ROS1/2, machine learning, computer vision Excellent
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mechanical engineering with specialization in mechanical, manufacturing or related areas. Employment of CAD-CAE-CAM tools, FEM simulation resources. Experience with additive manufacturing. Necessary
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, metamaterials, and/or soil–structure interaction, and proven skills in experimental design and testing as well as numerical modelling (e.g., FEM). Experience with railway dynamics, soil mechanics, or nonlinear
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related to staff position within a Research Infrastructure? No The open position is posted on the website (https://lmaa.pesquisa.ufabc.edu.br/edital-de-selecao-pos-doutorado-fapesp/ ) and also at Fellowship