There is a fully funded PhD opportunity available at the Auckland Bioengineering Institute (ABI) in New Zealand in the area of personalized models of upper limb disorders. ABI is a world-leading research institute that aims to improve medical diagnosis and treatment of injury and disease. We do this through the application of engineering sciences and technical innovation to medicine and human physiology.
Movement disorders that affect the upper limb are common, and place a large burden on society. Stroke and brachial plexus injuries, for example, result in partial limb paralysis and lifelong deficits in function. Clinicians currently diagnose and treat these disorders using qualitative assessment, including observational movement analysis and subjective clinical tests, based on knowledge and intuition-based interpretation. This ‘evidence-based’ approach determines the efficacy of a treatment strategy on a patient cohort, without acknowledging that individuals within that cohort respond differently to each intervention.
The project aims to develop a personalised approach to quantitatively assess, treat, and monitor upper limb disorders, using computational models, wearable sensors, and robotic devices. The interpretation of movement patterns will be performed using biomechanical simulation and data-driven machine learning classification to assist clinical decision-making and personalised treatment plans. This project is part of a large project grant called 12 Labours, tasked with building computational models of the human body into clinical workflows for diagnosis and treatment plan in NZ.
This project would suit someone with a master’s degree in biomedical engineering, mechanical engineering, exercise science or related field. Strong background in computational modelling or movement science is recommended. Some experience with signal processing and robotic would be desirable but not essential.
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 Professor Thor Besier. Application are now open and will close July 1st. If you are interested in joining our team, please email a letter of interest and CV to j.choisne@auckland.ac.nz
Movement disorders that affect the upper limb are common, and place a large burden on society. Stroke and brachial plexus injuries, for example, result in partial limb paralysis and lifelong deficits in function. Clinicians currently diagnose and treat these disorders using qualitative assessment, including observational movement analysis and subjective clinical tests, based on knowledge and intuition-based interpretation. This ‘evidence-based’ approach determines the efficacy of a treatment strategy on a patient cohort, without acknowledging that individuals within that cohort respond differently to each intervention.
The project aims to develop a personalised approach to quantitatively assess, treat, and monitor upper limb disorders, using computational models, wearable sensors, and robotic devices. The interpretation of movement patterns will be performed using biomechanical simulation and data-driven machine learning classification to assist clinical decision-making and personalised treatment plans. This project is part of a large project grant called 12 Labours, tasked with building computational models of the human body into clinical workflows for diagnosis and treatment plan in NZ.
This project would suit someone with a master’s degree in biomedical engineering, mechanical engineering, exercise science or related field. Strong background in computational modelling or movement science is recommended. Some experience with signal processing and robotic would be desirable but not essential.
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 Professor Thor Besier. Application are now open and will close July 1st. If you are interested in joining our team, please email a letter of interest and CV to j.choisne@auckland.ac.nz