Research FELLOW - DOE Genesis Forward Modeling Project

Applications should be sent to abucsek with the subject line:
Postdoctoral Application - DOE Genesis Forward Modeling Project.

Interested applicants should submit:

• Cover letter describing research interests and relevant experience (or information embedded in email).
• Contact information for three references.

At Michigan Engineering, we develop the talent and technologies that move society forward and serve our state and national interests. Through discovery and innovation, we create the foundational knowledge and practical technologies to solve not only today's most pressing challenges, but also power industries and change lives. Our programs and community are designed to promote personal well-being and achievement - enabling everyone to unlock their potential and contribute with confidence.

The Department of Mechanical Engineering at the University of Michigan invites applications for a postdoctoral research fellow. The position is part of a U.S. Department of Energy Genesis Mission project that brings together the University of Michigan, Los Alamos National Laboratory, and Argonne National Laboratory to accelerate materials discovery by integrating advanced 3D X-ray diffraction experiments, mechanistic modeling, and artificial intelligence.

A powerful set of high-resolution 3D X-ray diffraction imaging modalities - topotomography, dark-field X-ray microscopy, and Bragg coherent diffraction imaging - has emerged over the past decade that can resolve 3D defect architectures and strain fields with spatial resolutions approaching tens of nanometers. However, current reconstructions are slow, expert-driven, and difficult to scale, preventing real-time experimental decision-making and broader use for materials design.

To address this challenge, the project will combine molecular dynamics-generated synthetic microstructures, physics-based forward diffraction models, and generative AI approaches such as variational autoencoders and diffusion models. The resulting workflow will train AI models on paired virtual diffraction data and known ground truth, then validate and refine them using experimental datasets from DOE light sources. The postdoctoral fellow will focus on curating the virtual diffraction models and datasets, eventually extending into real experiments and experimental datasets collected at the Advanced Photon Source.

The successful candidate will:

• Develop physics-based forward models for diffraction-based materials characterization, including topotomography, dark-field X-ray microscopy, and Bragg coherent diffraction imaging. Many of these forward models exist to varying degrees of readiness, but the postdoc will be responsible for curating these models in preparation for the project.
• Simulate diffraction patterns from synthetic 3D crystalline microstructures (provided by collaborators at LANL).
• Integrate forward models with experimental data streams from the Advanced Photon Source and conduct new experiments at these facilities.
• Collaborate with AI/ML researchers to incorporate forward models into inverse modeling, uncertainty quantification, autonomous analysis, and surrogate modeling frameworks.
• Work closely with experimental collaborators at the University of Michigan, Los Alamos National Laboratory, and the Advanced Photon Source.
• Contribute to publications, conference presentations, software development, and project reporting.
• Participate in a highly collaborative, multidisciplinary research environment spanning mechanics, materials science, X-ray characterization, scientific computing, and artificial intelligence.

Applicants should have:

• A Ph.D. in mechanical engineering, materials science and engineering, applied physics, computational science, or a closely related field.
• Strong background in solid mechanics, materials physics, and crystallography.
• Experience developing tools using Python, C/C++, MATLAB, etc.
• Demonstrated ability to conduct independent research and publish in peer-reviewed journals.
• Strong communication skills and interest in collaborative, team-based research.

Preferred candidates will have experience in one or more of the following areas:

• 3D X-ray diffraction, high-energy diffraction microscopy, Bragg coherent diffraction imaging, dark-field X-ray diffraction, X-ray diffraction, or other diffraction-based characterization methods.
• Reconstructing, forward modeling, or inverse modeling of diffraction data.
• High-performance computing and scalable scientific software development.
• Molecular dynamics, crystal plasticity, finite-element, or other 3D mesoscale materials modeling.

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the…