A PhD position will be available at University of Pavia in Italy starting November 2025. 

Interested candidates are encouraged to contact Prof. Giulia Scalet (giulia.scalet [at] unipv.it).

The candidate will work on new computational approaches for the simulation of smart polymers and hydrogels and their application to mechanobiology studies. 

Extreme Mechanics Letters (EML) is thrilled to announce the appointment of Professor Xuanhe Zhao of the Massachusetts Institute of Technology (MIT) as Co-Editor-in-Chief of EML. Professor Zhao is a world-renowned expert in the mechanics of materials and soft robotics.

A compliantly fixed hemispherical indenter in adhesive contact with an elastic sample firmly bonded to a rigid base is considered under the assumption that the rigid base undergoes small-amplitude high-frequency normal (vertical) oscillations. A general law of the rate-dependent JKR-type adhesion is assumed, which relates the work of adhesion to the contact front velocity. Using the Bogoliubov averaging approach in combination with the method of harmonic balance, the leading-order asymptotic model is constructed for steady-state vibrations.

Dear members of the iMechanica community,

The deadline for abstract submission for the 
EuroSuperalloys - THE symposium for all things superalloy,
including modeling, DFT,  atomistic simulations and machine learning approaches for 
superalloys and metallic or intermetallic materials beyond superalloys -
is approaching fast: 31. March 25

For more information, see:
https://eurosuperalloys.sciencesconf.org/?lang=en

Looking forward to your contributions!

Erik

Are you passionate about solid mechanics and intrigued by machine learning? We are seeking a qualified candidate who can merge expertise from both fields to develop innovative tools for analyzing deformation and fracture in solid materials.

Expected start date and duration of employment

This is a 1-year position starting on 15 August 2025 or as soon possible thereafter.

USACM Student Chapter Monthly Seminar.

Thursday, March 27, at 4PM - 5PM (Eastern time - New York). 

Speaker: Yifan Du, Johns Hopkins University

Title: The Evolutional deep neural network for time dependent PDEs

Fusion-based manufacturing techniques, such as laser welding and additive manufacturing, are revolutionising how we produce complex components across industries. Yet, one critical challenge persists: how do we reliably control and predict melt-pool behaviour to ensure high-quality outcomes? This question was at the heart of my PhD research, completed at Delft University of Technology in the Netherlands.

I am pleased to share our newest open-access article just published in #ActaMaterialia.