Sujets de thèses
Ph.D. position in mechanical modeling of the muscle -- MR Elastography and multiscale modeling of the mechanical properties of the skeletal muscle
The mechanical behavior of muscle tissue under mechanical loading is the result of active and passive mechanisms within their constituents and at interfaces, as well as the arrangement of these constituents. One of the most efficient ways to describe the overall behavior of a muscle structure through the different scales of its components is to model the tissue by finite element modeling including a mechanical law with multi-scale parameters by homogenization methods. An innovative link between microscopic experimental mechanical properties (by tensile tests) on isolated ex vivo muscle fibers and macroscopic mechanical behavior of the muscle in vivo at the millimeter scale (in vivo imaging by Magnetic Resonance Elastography - MRE) will be proposed. This link will be made through the development of an anisotropic macroscopic Numerical Finite Element Model of muscle tissue integrating a mechanical law taking into account the distribution of muscle microstructures as well as the mechanical laws of each of the constituents allowing the homogenization of the fibrous microstructures of muscle tissue (identified experimentally). Thus, the successful candidate will have to: 1) Set up a homogenized anisotropic mechanical behavior law of the muscle tissue; this law will have to make the link between the microscopic mechanical properties of isolated muscle fibers and macroscopic mechanical properties of muscles isolated from mice with the mechanical behavior in vivo measured by magnetic resonance elastography. (2) Implementing this law of behavior in a finite element model of skeletal muscle. (3) This modelling of the micro-macro links will finally be used by the candidate for application to the elucidation of the role of the KLF10 gene on the development of the musculo-tendinous system via a preclinical study on mice by MRI. This work will include a stage of development of muscular MRE on small animal (7T) MRI (animal model lacking the KLF10 gene).
This multidisciplinary subject requires skills in both biology / physiology but also in the laws of mechanical behavior applied to living organisms and their identification on experimental in and ex vivo measurements. The selected candidate should have a strong taste for these different experimental and numerical disciplines. The knowledge of Matlab is essential. As for any research project and considering the international collaboration proposed, a very good command of English is essential. Starting time: September 1rst, 2020
The thesis is in collaboration between the BMBI (UTC Compiègne) and ICube (University of STrasbourg, France) and will be co-directed and will take place between the two laboratories.
For applying send the following documents:
- Cover letter
- Grades of Master
Open PhD Position in Computer Vision/Deep Learning for Healthcare Sponsored by Intuitive Surgical
The operating room is a high-tech environment in which the surgical devices generate a lot of data about the underlying surgical activities. Our research group aims at making use of this large amount of multi-modal data coming from both cameras and surgical devices to develop an artificial intelligence system that can assist clinicians and staff in the surgical workflow. In this context, we currently have a new PhD position at the University of Strasbourg that will focus on developing machine learning and computer vision methods to understand the scene of the operating room, recognize the human activities, and analyze the workflow. The project will use as input multi-view RGB-D videos capturing surgical activities.
As this PhD position is funded by a fellowship from Intuitive Surgical, the successful candidate will have the opportunity to interact with researchers from Intuitive Surgical and also to conduct internships at the company in Sunnyvale, California.
More information is available here