Dear colleagues,
I am pleased to invite you to the next webinar in the Extreme Mechanics Letters (EML) Webinar Series.
Our upcoming webinar will be delivered by Prof. Ritu Raman (MIT):
"Tissue Engineering Biological Actuators for Biohybrid Robots"
Date: Thursday, November 5, 2026
Time: 10:00 a.m. Boston / 3:00 p.m. London / 4:00 p.m. Paris / 11:00 p.m. Beijing
Discussion leader: Prof. Taher Saif (UIUC)
I submitted the manuscript "An Archard-type multiscale theory of hysteretic friction on viscoelastic half-planes, built on exact per-scale viscoelastic contact solutions" for consideration as a Regular Article.
Are you passionate about advancing subsurface technologies for the energy transition? I am seeking outstanding Ph.D. students and postdoctoral researchers to join my research team. Opportunities span theoretical, numerical, and experimental research. A strong background in mechanics is required.
Please see the flyer for more information!
Prof. Chloé Arson, incoming Eddie Goldenberg Canada Research Chair in Subsurface Energy Systems and Geomechanics at McGill University.
Are you interested in scientific computing, artificial intelligence, and how they can automate and enhance design of civil engineering structures? Are you interested in creating societal impact with your research? Then the Department of Civil and Architectural Engineering of Aarhus University invites you to apply for this position.
The expected starting date is no later than August 1 2027.
The Mehmani Research Group, Department of Energy and Mineral Engineering
The Pennsylvania State University, University Park
The Ira A. Fulton Schools of Engineering at Arizona State University (ASU) and the School for Engineering of Matter, Transport and Energy (SEMTE) seek applicants for a tenure-track or tenured faculty position in Materials, Mechanics, and Processing for Microelectronic Packaging. The search addresses the materials, processing, and mechanics that determine how packaged microelectronic systems are built and how they perform.
Dear iMechanica community,
Scientific Machine Learning (SciML) combines scientific knowledge, mathematical models, and data to address scientific and engineering problems. For the mechanics community, potential applications include predicting thermal and mechanical fields, identifying material parameters from measurements, and developing fast surrogates for expensive numerical simulations.
