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biomechanics

Fully funded doctoral course position

Submitted by Daisuke Ishihara on

Fully funded doctoral course position is available for Computational Multi-Physics Coupled Analysis Laboratory from iART Program of Kyushu Institute of Technology, Japan. One successful candidate will carry out his research in the area of biomechanics and biomimetics using computational mechanics.

Fully funded doctoral course position

Submitted by Daisuke Ishihara on

Fully funded doctoral course position is available for Computational Multi-Physics Coupled Analysis Laboratory from iART Program of Kyushu Institute of Technology, Japan. One successful candidate will carry out his research in the area of biomechanics and biomimetics using computational mechanics.

Journal Club for January 2024: Machine Learning in Experimental Solid Mechanics: Recent Advances, Challenges, and Opportunities

Submitted by Hanxun Jin on

Hanxun Jin (a,b), Horacio D. Espinosa (b)
a Division of Engineering and Applied Science, California Institute of Technology
b Department of Mechanical Engineering, Northwestern University

In recent years, Machine Learning (ML) has become increasingly prominent in Solid Mechanics. Its diverse applications include extracting unknown material parameters, developing surrogate models for constitutive modeling, advancing multiscale modeling, and designing architected materials. In this Journal Club, we will focus our discussion on the recent advances and challenges of ML when experimental data is involved. With broad community interest, as reflected by the increasing number of publications in this field, we have recently published a review article in Applied Mechanics Reviews titled “Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review”. Moreover, a recent insightful paper from Prof. Sam Daly’s group also discussed some perspectives in this field. In this Journal Club, we would like to introduce and share insights into this exciting field.

PhD positions in cancer biomechanics at the University of Galway, Ireland

Submitted by EoinMcEvoy on

Applications are invited from suitably qualified candidates for full-time, fully-funded PhD positions at the University of Galway, Ireland. Researchers will investigate the mechanics and mechanobiology of tumour growth and therapy resistance. These positions are funded by a European Research Council Starting Grant and will be under the supervision of Dr Eoin McEvoy, Assistant Professor in Biomedical Engineering. For more information, please see the attached advert.

Fully funded PhD positions in Cardiovascular Engineering (start Jan. 2024 or later)

Submitted by brunorego on

Description: The Cardiovascular Engineering Lab (CEL) is actively recruiting multiple graduate students interested in pursuing a PhD in Biological Engineering or Engineering Science at Louisiana State University (LSU). Research focus is flexible, depending on the strengths and interests of the applicant. Projects at CEL encompass both experimental studies of cardiovascular biology and mechanics as well as computational modeling and simulation of cardiovascular function.

PhD and Master’s Positions in Soft Tissue Mechanics

Submitted by Y.Jason.Hua on

The LESION (CENTRAL NERVOUS SYSTEM BIOMECHANICS) Laboratory at the University of Mississippi's Department of Biomedical Engineering is seeking graduate students (PhD, MSc).

The LESION Lab aims to develop imaging and modeling tools for the understanding, diagnosis, and treatment of central nervous system disorders, with a particular focus on diseases related to the eye and brain, such as glaucoma and traumatic brain injury.

Postdoc in mechanics of woven and fiber-based materials at the University of Pittsburgh

Submitted by iasigal on

We are looking for a highly motivated postdoc to join our team to study the mechanics of woven or fiber-based materials. Applicants should have expertise in mechanics of materials with long fibers. These can be artificial, like textiles and fabrics, or natural, like soft tissues including tendon or heat valves.  Experience in multi-scale methods is advantageous.  Experimental or computational are both welcome.