Postdoctoral Associate – Topology Optimization, DfAM (Design for Additive Manufacturing), FEM (Finite Element Analysis), CFRP
- Queen's University
- Location: Kingston, Canada
- Job Number: 7071907
- Posting Date: Nov 6, 2020
- Application Deadline: Dec 6, 2020
Job DescriptionFunctional Area: Research, Mechanical Design, Software / App. Development
Department: Mechanical and Materials Engineering, Queen’s University, Canada
Lab: Structural and Multidisciplinary Systems Design Lab (SMSD)
Employment Type: Full-Time
POSTDOCTORAL ASSOCIATE, Structural and Multidisciplinary Systems Design Lab, to support, expand, and develop methodologies and computational analysis/design tools across various research projects including: topology optimization (TO); design for additive manufacturing or 3D printing (DfAM); multi-material topology optimization (MMTO) including numerical optimization of joints for dissimilar materials for lightweight design; nonlinear finite element analysis (NL-FEA or NL-FEM) including numerical modeling of crash analysis and optimum design; machine learning (ML) or artificial intelligence (AI); packaging optimization (PO); and modeling and optimal design of carbon fiber reinforced plastic (CFRP).
Apply linear and non-linear modeling, analysis, and multi-physics finite element methods to characterize mechanical system responses. Optimize mechanical system responses through advanced multi-disciplinary optimization (MDO), multi-physics, multi-objective optimization (MOO) methodologies.
Incorporate knowledge of practical design and manufacturing for part-level and system-level prototyping. Contribute to active industry projects in the automotive, aerospace, energy, and defense sectors. Opportunity to apply machine learning / deep learning.
• PhD in Mechanical Engineering, Aerospace Engineering, Mathematics, Materials Engineering, or equivalent.
• Familiarity with design optimization, topology optimization, and/or MDO (multidisciplinary optimization)
• Familiarity with finite element method (FEM) or computational fluid dynamics (CFD)
• Proficiency with software engineering with Python, and/or Fortran, and/or C++.
• Experience with reading, interpreting, and modifying third-party software code.
• Experience with finite element analysis (ANSYS, and/or HyperWorks, and/or Abaqus, and/or LS-DYNA).
• Excellent interpersonal, written and verbal communication skills.
• Research experience with numerical optimization, and/or sensitivity analysis, and/or finite element method (FEM).
• Record of peer-reviewed publications.
The Structural and Multidisciplinary Systems Design Lab (SMSD) at Queen’s University is a leading research organization that specializes in advanced multidisciplinary optimization (MDO) and multiobjective optimization (MOO); topology optimization (TO); design for additive manufacturing or 3D printing (DfAM); modeling and optimal design of carbon fiber reinforced plastic (CFRP); multi-material topology optimization (MMTO) including numerical optimization of joints for dissimilar materials for lightweight design; nonlinear finite element analysis (NL-FEA or NL-FEM) including numerical modeling of crash analysis and optimum design; machine learning (ML); and packaging optimization (PO).
This state-of-the-art research body has extensive experience in developing and publishing novel academic research for automotive, aerospace, energy, and defence driven applications, utilizing analytical and computational optimization techniques to develop new principles and methodologies that solve practical problems with various industrial partners. Dr. Il Yong Kim’s SMSD group is currently seeking talented candidates to apply for Postdoctoral Associate positions who are interested in contributing to advanced research programs.
Active industry partners in four sectors (aerospace, automotive, defense, energy) including: General Motors; Magna International; General Dynamics Canada; Bombardier Aerospace; Pratt & Whiney Canada; Safran Landing Systems; Bombardier Transportation; and National Research Council.