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Collaborative research project supported by five industrial partners with active research and development programs in the aerospace, fire safety and transport electrification sectors. The problems of fire resistance for batteries and PMCs used as firewalls share many similarities. In both cases, fire-driven failure is often controlled by feedback loops between the heat-driven outgassing of the solid material (be it the PMCs or a battery) and the gas-phase reaction of the combustible species exiting the surface exposed to fire.

The lab of Wave Engineering for eXtreme and Intelligent matTEr (We-Xite) has multiple openings for Ph.D. positions. We are looking for exceptional and highly motivated candidates with background in Engineering, Physics, Materials or Mathematics. The research will have a balance between experimental characterizations (non-destructive evaluation of samples fabricated using additive and subtractive methods), numerical simulations (finite element modeling) and analytical derivations (nonlinear dynamics of spring-mass systems).

The lab of Wave Engineering for eXtreme and Intelligent matTEr (We-Xite) has multiple openings for Ph.D. positions. We are looking for exceptional and highly motivated candidates with background in Engineering, Physics, Materials or Mathematics. The research will have a balance between experimental characterizations (non-destructive evaluation of samples fabricated using additive and subtractive methods), numerical simulations (finite element modeling) and analytical derivations (nonlinear dynamics of spring-mass systems).

 Applications are invited for Ph.D. (Spring or Fall 2022) and/or postdoctoral (ASAP) positions in the group of J. Hanna in Mechanical Engineering at the University of Nevada, Reno.  We are a theoretically oriented group that also engages in experimental work, with broad general interests in classical mechanics and applied geometry (see cmag.neocities.org ).  We are fully in-person-operational.

Possible topics include:

Dear Colleague,

I would be most grateful if you could advertise and promote the exciting news that the Department of Mechanical Engineering at UC Berkeley is currently seeking applications for a pair of tenure-track faculty positions: 

Our views on how one can leverage machine learning techniques to help constitutive modeling of composite materials are summarized in this paper

Xin Liu, Su Tian, Fei Tao and Wenbin Yu, A review of artificial neural networks in the constitutive modeling of composite materials, Composites Part B, vol. 224, 2021,109152. 

https://www.sciencedirect.com/science/article/pii/S1359836821005321.