ORGANISATION/COMPANYUniversité Gustave Eiffel
RESEARCH FIELDMedical sciences › Other
RESEARCHER PROFILEFirst Stage Researcher (R1)
APPLICATION DEADLINE21/03/2022 17:00 - Europe/Brussels
LOCATIONFrance › Marseille
TYPE OF CONTRACTTemporary
HOURS PER WEEK35
OFFER STARTING DATE01/10/2022
EU RESEARCH FRAMEWORK PROGRAMMEH2020 / Marie Skłodowska-Curie Actions COFUND
MARIE CURIE GRANT AGREEMENT NUMBER101034248
Spinal cord injury affects between 250,000 and 500,000 people each year. It is usually caused by a spinal cord compression due to medullar canal narrowing (eg: intervertebral disc swelling) or the penetration of vertebral bone fragment resulting from fractures (Burst). One of the main challenges following a trauma is to assess neurological damage in order to predict recovery and guide injury management.
Finite element (FE) models of the spinal cord are often used to investigate spinal cord injuries, and mechanical parameters such as stresses and strains of tissues are used to predict injury risk. The relevance of the model's prediction relies on the characterization of the tissue’s mechanical properties and especially on the material properties of gray and white matter (Fournely et al. 2020). In most spinal cord models, these materials are considered homogeneous, non-viscoelastic and their behavior is based only on tensile tests (Bailly et al. 2021, Ichihara et al. 2001). However, many studies have shown that in the brain these tissues presented a non-homogeneous, non-linear, viscoelastic behavior (Ramo et al. 2018), strongly dependent on loading conditions (compression, tension, shear), on drainage conditions (confined or not) and on strain rate (Budday et al. 2019).
Recent studies, carried out at several scales (axial compression, micro-indentation) were able to characterize and discriminate the behavior of white and gray matter and to corelate white mater rigidity variations with axonal microstructure (Weickenmeier et al. 2017). However, these improved knowledges have not yet translated into an improved spinal cord FE models. Moreover, the effect of local properties variations within the spinal cord on the risk of injury has not yet been investigated.
The objective of this project is to improve a numerical model of spinal cord in order to assess the effect of local mechanical properties variations and viscoelasticity on the prediction of the risk of neurological injuries. The project will be broken down into three sub-objectives:
Objective 1. Modeling the local behavior of the white and grey matter.
Indentation tests performed in the laboratory will be numerically reproduced using a materials law initially developed for human brain tissue (Budday et al. 2017). This viscoelastic Ogden model includes six parameters (1 elastic stiffness, 2 viscoelastic stiffnesses, 1 non-linearity parameter and 2 viscous time constants). Inverse method will be use to find the elastic stiffness and viscoelastic stiffness parameters to best fit indentation results. First, sets of parameters will be developed for each areas of the spinal cord. Second, the parameters of the material law will be defined according to the structure of the indented tissues (myelin level, axonal density, etc.).
Objective 2. Modeling the overall behavior of the cord.
Published confined axial compression (Yu et al. 2019), transverse compression (Fradet et al. 2016) and relaxation tests on porcine spinal cord will be reproduced numerically using the material properties previously obtained. The effect of local refinement of material parameters (considering white and gray matter, microstructure, viscoelasticity, etc.) on the overall behavior of the cord will be evaluated.
Objective 3. Correlating the mechanical response of the spinal cord to neurological damage.
The stress and strain in the spinal cord model will be used to predict neurological lesions. For this, the injury threshold will be defined by reproducing porcine spinal cord impacts carried out at different speeds (Kim et al. 2018) and showing different injury severities. The effect of accounting for the microstructure in the modeling of the spinal cord on the prediction of the lesion will be evaluated by experimental design. Finally, the refined spinal cord model will be used to reproduce real cases of Burst-type fracture (Diotalevy et al. 2020) and predict the risk of injury. The prediction of the refined model will be evaluated in regard to the actual injury of patients and their recovery."
This thesis will be in cosupervision (cotutelle) with École de Technologie supérieure de Montréal (Canada). For more information, please contact the PhD thesis supervisor.
- High-quality doctoral training rewarded by a PhD degree, delivered by Université Gustave Eiffel
- Access to cutting-edge infrastructures for research & innovation.
- Appointment for a period of 36 months based on a salary of 2 700 € (gross salary per month).
- Job contract under the French labour legislation in force, respecting health and safety, and social security: 35 hours per week contract, 25 days of annual leave per year.
- International mobility will be mandatory
- An international environment supported by the adherence to the European Charter & Code.
- Access to dedicated CLEAR-Doc trainings with a strong interdisciplinary focus, together with a Career development Plan.
- At the time of the deadline, applicants must be in possession or finalizing their Master’s degree or equivalent/postgraduate degree. At the time of recruitment, applicants must be in possession of their Master’s degree or equivalent/postgraduate degree which would formally entitle to embark on a doctorate.
- At the time of the deadline, applicants must be in the first four years (full-time equivalent research experience) of their research career (career breaks excluded) and not yet been awarded a doctoral degree. Career breaks refer to periods of time where the candidate was not active in research, regardless of his/her employment status (sick leave, maternity leave etc). Short stays such as holidays and/or compulsory national service are not taken into account.
- At the time of the deadline, applicants must not have resided or carried out their main activity (work, studies, etc.) in France for more than 12 months in the 3 years immediately prior to the call deadline.
- Applicants must be available to start the programme on schedule (around 1st October 2022).
- Please refer to the Guide for Applicants available on the CLEAR-Doc website.
- The First step before applying is contacting the PhD supervisor. You will not be able to apply without an acceptation letter from the PhD supervisor.
- Please contact the PhD supervisor for any additional detail on job offer.
- There are no restrictions concerning the age, gender or nationality of the candidates. Applicants with career breaks or variations in the chronological sequence of their career, with mobility experience or with interdisciplinary background or private sector experience are welcome to apply.
- Support service is available during every step of the application process by email: email@example.com
Web site for additional job details
REQUIRED LANGUAGESFRENCH: GoodENGLISH: Good
- At the time of the deadline, applicants must be in possession or finalizing their Master’s degree or equivalent/postgraduate degree.
- At the time of recruitment, applicants must be in possession of their Master’s degree or equivalent/postgraduate degree which would formally entitle to embark on a doctorate.
EURAXESS offer ID: 718012
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