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A paediatric-population atlas to rapidly generate subject-specific models of common orthopaedic hip and knee conditions in children
Within the Musculoskeletal Modeling Group at the Auckland Bioengineering Institute in New Zealand, we are looking for a motivated PhD candidate to participate in ongoing research on building and validating a paediatric-population atlas of lower limbs to generate patient-specific models of children with Cerebral Palsy.
Research Group
The Musculoskeletal Modelling Group is internationally known for developing statistical shape models of adult bones to understand the shape variation across the population. We developed the Musculoskeletal Atlas Project (MAP) an open-source software platform, to generate personalized computational models of the musculoskeletal system in the adult population. This population-based atlas contains imaging and functional data obtained from hundreds of adults, but has not yet been extended to a paediatric population. The scientific and paediatric clinical community would benefit greatly from a paediatric population-based anatomical and functional atlas that is capable of predicting the form-function relationships of the musculoskeletal system.
The objectives of this position will be to build a paediatric population atlas using machine-learning algorithm and validate its capability to 1) predict bone geometry of children with cerebral palsy from routine clinical imaging and 2) generate subject-specific neuro-musculoskeletal models of children with CP based on the atlas bone prediction.
Responsibilities
You will build a statistical shape model of paediatric tibia, femur and pelvis bones of children from 4 to 18 yo using machine learning algorithms (PCA, PLSR etc…)
You will collect and post-process MR images and 3D gait analysis in children with CP to generate subject-specific neuro-musculoskeletal models
You will provide administrative and technical support of activities within the research group, department or faculty.
Profile
This position is open for interested PhD candidates with an interest in relating human movement science to medical images and musculoskeletal models.
The candidate must hold a master degree in biomedical/mechanical engineering or human movement sciences in which musculoskeletal modelling (OpenSim, AnyBody etc…), MRI or human motion analysis software (Nexus, V3D etc…) were used.
Excellent writing and oral communication in English is essential
Previous experience with in vivo measurements is of additional value.
Programming experience (i.e. Matlab, Python or similar software) is highly desirable but not necessary.
The candidate should be highly interested in working with children and in a multi-disciplinary environment consisting of engineers, physical therapists and orthopaedic surgeons.
Candidates planning their master thesis defense in summer 2019 are encouraged to apply.
Offer
This funded position include tuition and a competitive monthly stipend for 3-4 years. The student will work under the supervision of Dr. Julie Choisne and Associate Professor Thor Besier. Start date for this position is flexible but should start in 2019. If you are interested in joining our team, please email a letter of interest and CV to j.choisne@auckland.ac.nz
Within the Musculoskeletal Modeling Group at the Auckland Bioengineering Institute in New Zealand, we are looking for a motivated PhD candidate to participate in ongoing research on building and validating a paediatric-population atlas of lower limbs to generate patient-specific models of children with Cerebral Palsy.
Research Group
The Musculoskeletal Modelling Group is internationally known for developing statistical shape models of adult bones to understand the shape variation across the population. We developed the Musculoskeletal Atlas Project (MAP) an open-source software platform, to generate personalized computational models of the musculoskeletal system in the adult population. This population-based atlas contains imaging and functional data obtained from hundreds of adults, but has not yet been extended to a paediatric population. The scientific and paediatric clinical community would benefit greatly from a paediatric population-based anatomical and functional atlas that is capable of predicting the form-function relationships of the musculoskeletal system.
The objectives of this position will be to build a paediatric population atlas using machine-learning algorithm and validate its capability to 1) predict bone geometry of children with cerebral palsy from routine clinical imaging and 2) generate subject-specific neuro-musculoskeletal models of children with CP based on the atlas bone prediction.
Responsibilities
You will build a statistical shape model of paediatric tibia, femur and pelvis bones of children from 4 to 18 yo using machine learning algorithms (PCA, PLSR etc…)
You will collect and post-process MR images and 3D gait analysis in children with CP to generate subject-specific neuro-musculoskeletal models
You will provide administrative and technical support of activities within the research group, department or faculty.
Profile
This position is open for interested PhD candidates with an interest in relating human movement science to medical images and musculoskeletal models.
The candidate must hold a master degree in biomedical/mechanical engineering or human movement sciences in which musculoskeletal modelling (OpenSim, AnyBody etc…), MRI or human motion analysis software (Nexus, V3D etc…) were used.
Excellent writing and oral communication in English is essential
Previous experience with in vivo measurements is of additional value.
Programming experience (i.e. Matlab, Python or similar software) is highly desirable but not necessary.
The candidate should be highly interested in working with children and in a multi-disciplinary environment consisting of engineers, physical therapists and orthopaedic surgeons.
Candidates planning their master thesis defense in summer 2019 are encouraged to apply.
Offer
This funded position include tuition and a competitive monthly stipend for 3-4 years. The student will work under the supervision of Dr. Julie Choisne and Associate Professor Thor Besier. Start date for this position is flexible but should start in 2019. If you are interested in joining our team, please email a letter of interest and CV to j.choisne@auckland.ac.nz