NRC/ASEE Post-Doc Positions at the US Naval Research Laboratory in Computational Mechanics and Materials Science and Statistical Mechancis

Contact: Dr. Siddiq Qidwai, siddiq.qidwai@nrl.navy.mil

Postdoc Information: http://hroffice.nrl.navy.mil/jobs/postdoc.htm. Note the substantial stipend and benefits.

NOTE: US Citizenship is required for all positions. US Permanent Residents may be acceptable in certain circumstances.

Computational Mechanics/Multiphysics Vacancy:

The candidate for this position will have a strong educational and research background in computational mechanics and multiphysics. While experience in computational multiphysics is desired, it can be relaxed for a strong all-round background in mechanics. Examples of this background include, in mathematics: differential equations and functional analysis; in applied mechanics: continuum mechanics, plasticity, failure theories, and finite deformation and nonlocal frameworks; in computational mechanics: constitutive modeling, algorithmic development, nonlinear finite element method (FEM) and pertinent software (preferably Abaqus), code writing and scripting; and, if applicable, in multiphysics modeling: multifield interactions, functional couplings and pertinent software (preferably Comsol). The candidate should be at ease in using the abovementioned tools of the trade to solve computational problems involving single to multiple length scales (e.g., microscale fiber behavior to macroscale composite armor design) or coupling between different physics (e.g., mechanical, thermal, electrical, chemical, magnetic or mass transport). Specific topical experience in high-rate behavior of materials or biomechanics of the human body is strongly desired. The candidate will hold a PhD in mechanical engineering or related fields.

Computational Materials Science Vacancy:

The candidate for this position will have a strong educational and research background in computational materials science, with specific focus on experience at multiple length scales. Desired background in materials science includes: crystal plasticity, gradient plasticity, dislocation theory, defects in materials, and creep, damage and fatigue at the scale of the microstructure. Desired background in modeling includes: constitutive models of continuum plasticity, dislocation dynamics theory and simulation, multiscale methods, nonlinear finite element method (FEM) and pertinent software (preferably Abaqus), code writing and scripting. Experience in quasi-continuum bridging methods will be considered positively. The candidate should be at ease in using the abovementioned tools of the trade to solve computational problems involving single to multiple length scales (e.g., dislocation dynamics theory to crystal plasticity to phenomenological plasticity). The candidate should also be wailing to leverage the abovementioned knowledge to non-traditional materials, such as amorphous metals, soft magnetic materials, ceramics, etc. Familiarity with in situ scanning electron microscope (SEM) or transmission electron microscope (TEM) experimental methods and data is desired but not necessary. The candidate will hold a PhD in materials science and engineering or related fields.

Statistical Mechanics Vacancy:

The candidate for this position will have a strong educational and research background in computational mechanics, with focus on  using statistical, stochastic and reduced-order methods. Examples of a strong background include, in mathematics: statistics, stochastic process representation, partial differential equations, and functional analysis; in applied mechanics: continuum mechanics, statistical mechanics and inelasticity; and in computational mechanics: uncertainty modeling, propagation and quantification, stochastic constitutive models, reduced-order models (ROMs), Monte Carlo methods, deterministic and stochastic finite element method and pertinent software, code writing and scripting. The candidate should be at ease in using the abovementioned tools of the trade to develop stochastic constitutive models for crystal plasticity, uncertainty propagation in ROM biomechanics, and synthesis and analysis of Big Data (data analytics). Specific experience in inelastic material behavior, high-rate behavior of materials, or biomechanics of the human body is desired but not necessary. The candidate will hold a PhD in mechanical engineering or related fields.