Skip to main content

Blog posts

USACM Thematic Conference on Uncertainty Quantification for Machine Learning Integrated Physics Modeling

Submitted by jguilleminot_duke on

Dear Colleagues,

Abstract submission is still open for the USACM Thematic Conference on Uncertainty Quantification for Machine Learning Integrated Physics Modeling (MLIP) which will be held in Crystal City, Arlington, Virginia, August 18-19, 2022. The deadline for submission has been extended to May 15. More information can be found on the conference website. Please consider submitting and/or registering!

On behalf of the organizing committee, Johann

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.

Three-day intensive course "Invitation to nondestructive evaluation and structural health monitoring" by Zahra Sharif Khodaei, 24--26 May 2022, Czech Republic, Prague

Submitted by jenda_z on

I would like to bring to your attention an intensive three-day course "Invitation to nondestructive evaluation and structural health monitoring" that will be given by Dr. Zahra Sharif Khodaei (Imperial College London) from Tuesday, 24 May, to Thursday, 26 May 2022, at the Faculty of Civil Engineering, Czech Technical University in Prague.

PhD openings in Computational Solid Mechanics

Submitted by H.Chen on

The Computational Mechanics and Methods Group (CM3) in the Department of Mechanical Engineering at the University of Kentucky is seeking highly self-motivated individuals who have great interest in the broad research area of computational solid mechanics and methods. Ideal applicants should have strong background in solid mechanics and great interest in computational modeling & simulation. Related research experience in material failure modeling and simulation is a plus.