Université de Lorraine (Nancy, France) and the Centre National de Rééducation Fonctionnelle et de Réadaptation - Rehazenter (Luxembourg) are seeking for a PhD candidature in the field of musculoskeletal modelling and medical imaging. Musculoskeletal modelling has become in the last decades an alternative to invasive measurement methods to quantify musculo-tendon forces and related contributions to progression, support and balance, but also contributions to joint loading during dynamic tasks such as gait. However, the clinical application of such an approach remains limited due to a need for personalisation of the related models. The present project aims thus contributing in the field of clinical biomechanics by developing an integrated approach to achieve a multi-level ultrasound-based musculoskeletal model personalisation. The objective of this project is threefold and will focus the use of a lower limb musculoskeletal model to study normal gait as a starting benchmark case before targeting pathological cases: 1) Define a corrective method for soft tissue artefact, 2) Personalise joint kinematic models, 3) Gather primary ultrasound-based muscle parameters measurement in an integrated approach.
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The Kinesiology laboratory at University of Geneva (Geneva, Switzerland) has one open PhD studentship to define the intrinsic and extrinsic variability of pathological gait. The general goal of the project is to develop a neuromechanical models of human locomotion, together with Auke Ijspeert (Biorobotics laboratory, EPFL, BIOROB) and Alexandros Kalousis (machine learning, http://cui.unige.ch/~kalousis/) from the University of Geneva, in the framework of a collaborative Sinergia project funded by the Swiss National Science Foundation. The neuromechanical models will include numerical models of spinal cord circuits coupled to biomechanical simulations of the body. The purpose of the project is (1) to model pathological gait resulting from motor impairments such as cerebral palsy, and (2) to compare and combine neuromechanical simulation and machine learning approaches for gait analysis. The position is funded by SNSF for four years. The successful candidate will work in collaboration with 3 post-docs and 3 PhD Students that will be involved in the project.
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