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Wei Gao's blog

Postdoc and PhD positions at Texas A&M University

Submitted by Wei Gao on

One postdoc and multiple PhD positions are available at mechanical engineering at Texas A&M university in college station, Texas, working with Prof. Wei Gao. The research project will focus on mechanics and materials research with AI and machine learning approaches. The applicants are expected to have background in mechanics, physics or materials.

Postdoc and PhD positions at TAMU

Submitted by Wei Gao on

A postdoctoral associate and Phd positions are available at Mechanical Engineering at Texas A&M University with Prof. Wei Gao. Both positions can start as early as 8/16/2022. The research project will focus broadly on studying the mechanics of materials with multsicale modeling combined with AI and machine learning methods.  The work is highly interdisciplinary and involves collaborations with experimentalists at TAMU. You may read more about Prof. Gao’s research at www.gao-group.org.

Call for abstracts submission: USNC/TAM 2022: Mechanics of Multifunctional Low-dimensional Materials

Submitted by Wei Gao on

Dear colleagues,

We'd like to invite you to participate in the Minisymposium on "317-Mechanics of Multifunctional Low-dimensional Materials" at the 19th US National Congress on Theoretical and Applied Mechanics (USNC/TAM), to be held in Austin, Texas from June 19 to 24, 2022. The deadline for abstract submission is January 31 2022.

Call for abstracts: USNC/TAM 2022: Mechanics of Multifunctional Low-dimensional Materials

Submitted by Wei Gao on

Dear colleagues,

We'd like to invite you to participate in the Minisymposium on "317-Mechanics of Multifunctional Low-dimensional Materials" at the 19th US National Congress on Theoretical and Applied Mechanics (USNC/TAM), to be held in Austin, Texas from June 19 to 24, 2022. The deadline for abstract submission is January 31,2022.

Journal Club for November 2021: Machine Learning Potential for Atomistic Simulation

Submitted by Wei Gao on

 

Wei Gao

Department of Mechanical Engineering, University of Texas at San Antonio

 

In this journal club, we provide a brief summary on the concept, recent progress and tools of machine learning (ML) potential for atomistic materials modelling. We hope that it could benefit to the readers who are new to this filed and plan to develop their own or use others ML potentials. Comments and disscussions are welcomed. 

 

Postdoc in materials atomistic and multiscale modeling

Submitted by Wei Gao on

A postdoctoral associate position is available at University of Texas at San Antonio (UTSA) with Prof. Wei Gao, starting 9/1/2021. The candidate is expected to have a strong background in materials modeling, with at least one of the following skills: density functional theory, molecular dynamics, phase field method and machine learning. The research project will focus broadly on studying the phase transformation and related mechanical behavior in structural and functional materials.

Two Phd positions for 2020 Spring or Fall in Mechanical Engineering at UTSA

Submitted by Wei Gao on

Two fully funded PhD positions are available immediately in Dr. Wei Gao’s research group at The University of Texas at San Antonio (UTSA). The research will be on computational and experimental study on engineering and biological materials. UTSA is located in San Antonio, Texas, a vibrant city of more than 1.6 million people, with significant economic growth and numerous industrial establishments. The city and the University provide excellent cultural and educational opportunities as well as exceptional employment opportunities.

Post-doctoral Research Associate Position in Nanomechanics of Bone

Submitted by Wei Gao on

The Mechanics of Biological Materials/Structures Laboratory at the University of Texas at San Antonio (UTSA) is seeking to fill a Postdoctoral Research Associate position working on a NIH supported research project. In this five-year research project, we intend to elucidate the effect of proteoglycans on the age-related deterioration of bone quality and to develop therapeutic strategies for preventing or deterring such adverse effect.