Publisher
source

Northeastern University

Postdoctoral Research Associate in Informatics-Driven Mechanical Characterization of Solid and Porous Materials Northeastern University in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Postdoctoral research associate position supported by an NSF CMMI CDS&E award and industry-sponsored projects. Expected hiring range is $60,315.00 to $85,192.50. Northeastern University benefits package includes medical, vision, dental, paid time off, tuition assistance, wellness and life, retirement, and commuting/transportation benefits.

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Country

United States

University

Northeastern University

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Keywords

Computer Science
Mechanical Engineering
Materials Science
Aerospace Engineering
Civil Engineering
Solid Mechanics
Uncertainty Analysis
Computational Mechanics
Statistics
Constitutive Modeling
Foam
Image Correlation
Finite Element Analysis

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About this position

Postdoctoral Research Associate at Northeastern University in Burlington, Massachusetts, United States.

This position is for a postdoctoral researcher working on informatics-driven mechanical characterization of solid and porous materials. The project combines experimental mechanics and computational mechanics to build and validate a mechanics informatics framework supported by an NSF CMMI CDS&E award and industry-sponsored projects.

Research activities include designing and fabricating heterogeneous specimens, running multiaxial mechanical tests on a dual-actuator loading frame, and collecting full-field deformation data with three-dimensional digital image correlation (DIC). On the modeling side, the role involves automated finite element analysis, inverse identification of constitutive parameters, Bayesian optimization, and uncertainty quantification. About half of the work extends the framework to porous and cellular materials such as polymer and metal foams, plus mechanical testing and qualification of battery components.

Applicants should have a PhD in mechanical engineering, aerospace engineering, materials science and engineering, civil engineering, or a closely related field. The post also asks for experience in solid mechanics, constitutive modeling, nonlinear finite elements, Python programming, and familiarity with optimization, Bayesian inference, uncertainty quantification, or machine learning. Experience with DIC, specimen fabrication, Abaqus or similar tools, and experimental design is important. Preferred background includes battery materials, foams, or other porous/layered systems.

This is a research position with a salary range of $60,315 to $85,192.50 and a benefits package that includes medical, dental, vision, retirement, paid time off, tuition assistance, and commuting/transportation benefits.

To apply, submit the required resume through the Northeastern University Workday portal using the application link provided. No deadline was stated in the post.

Funding details

Postdoctoral research associate position supported by an NSF CMMI CDS&E award and industry-sponsored projects. Expected hiring range is $60,315.00 to $85,192.50. Northeastern University benefits package includes medical, vision, dental, paid time off, tuition assistance, wellness and life, retirement, and commuting/transportation benefits.

What's required

PhD in mechanical engineering, aerospace engineering, materials science and engineering, civil engineering, or a closely related field. Zero to three years of relevant research experience in experimental and/or computational solid mechanics. Knowledge of solid mechanics and continuum constitutive modeling, including anisotropic elasticity, plasticity, and porous or cellular materials. Ability to conduct mechanical testing on electromechanical or servo-hydraulic load frames and use digital image correlation. Experience designing and executing experiments on heterogeneous specimen geometries, including fabrication, instrumentation, and documentation. Knowledge of nonlinear finite element analysis and experience with Abaqus or similar codes, including user-defined material subroutines. Ability to program in Python and build automated simulation, data-processing, and inverse-identification workflows. Familiarity with optimization, Bayesian inference, uncertainty quantification, or machine learning for engineering problems. Ability to analyze data, publish peer-reviewed papers, and present to academic and industrial audiences. Preferred experience includes battery components, foams, or other porous and layered materials.

How to apply

Apply through the Northeastern University Workday job portal using the provided application link. Submit the required resume and any other requested materials through the online application system.

More information can be found here

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