Adolescent Idiopathic Scoliosis (AIS) is a 3D deformity of the spine affecting previously healthy
children, substantially reducing their quality of life and creating a life-long burden of disease.
Till now, no curative treatment exists partly because its cause and disease mechanism are still
unknown. In this ERC funded project, we will uncover whether a complex perfect storm of
anatomical, biomechanical and mechanobiological causes in the intervertebral disc are
responsible AIS.

During the adolescent growth spurt, many changes are occurring in our spines. If tissue
maturation is not matched by increasing loads and changes in shape, this could lead to spinal
instability and excessive tissue strains. Until now this was not possible to study because AIS
only occurs in human children and there were no safe methods to image their spines
repeatedly during growth. In the ERC project, we are running a clinical study using newly
developed MRI-based synthetic CT imaging to collect such information in normal and AIS
children.

In this PhD research, we will first develop methods to generate subject-specific FE spine
models. These will be based on a combination of landmark recognition, statistical
shape/appearance modeling and machine learning methods. Once validated against imaging
and biomechanical data from cadaveric spines, subject-specific multi-scale motion segment
and spine models will be generated from the imaging data to explore spinal instability and
intervertebral disc deformations during growth in the children of the clinical study.

The PhD candidate will contribute to a multi-disciplinary team of biomedical engineers, imaging
scientists and spine surgeons, from the student to senior level, working on engineering,
biological, imaging and clinical studies. An educational and professional development program
is offered to all PhD candidates. You will also be involved in teaching courses, as well as
contribute to the supervision of bachelor and master students. Based on your research, you
will be expected to present at conferences, publish in scientific journals and write a doctoral
dissertation.

More information:

The multidisciplinary institute of Medical and Biological Engineering at the University of Leeds is seeking a PhD applicant to study the effect of bleeding disorders on bone and joints biomechanics. The successful candidate will contribute to computational models of bone and joints, and assess how bone biology is affected by bleeding disorders. They will have a strong background in computational mathematics or engineering. More information available at https://phd.leeds.ac.uk/project/1388-an-engineering-approach-to-assess-effect-of-bleeding-on-bone-for-patients-with-bleeding-disorders.

Please contact Dr Marlène Mengoni (m.mengoni@leeds.ac.uk) before applying online.

The LS2P laboratory (from its French name, Laboratoire des Systèmes Portés par la Personne) develops non-invasive devices for measuring physiological parameters such as heart rate, oxygen saturation or blood pressure. A strong integration is a key factor from the design stage of the sensors. This allows them to be integrated into bracelets, patches or headbands to make them compatible with their daily use. The robustness of the measurement is a key factor in the relevance of these devices. It is obtained thanks to sensor technology and the performance of on-board signal processing algorithms. It also requires a good understanding of the physiology of the person faced with the disturbances encountered in daily life. The design of these devices is based on the development and use of numerical models to simulate the behavior of the human body. The doctoral student will integrate the "pôle avatar numerical" team of the laboratory to study a deformable 3D model of the forearm and its vascular system. Digital signatures will then be defined to assess the influence of the persons position and movements on the dynamics of the vascular system. The results obtained will be validated by the analysis of experimental data. We are looking for a candidate with a solid experience in mechanics and numerical modeling (CFD, FEM). Good programming skills are required and preferably previous experience in the development of computational mechanics tools. Motivation and interest in bioengineering is recommended. Excellent knowledge of written and spoken English is required.

More information: 
https://www.theses-postdocs.cea.fr/offre-de-emploi/emploi-signatures-numeriques-du-systeme-cardiovasculaire-de-l-avant-bras_20149.aspx