The Rehabilitation Engineering and Robotics laboratory at UCD has an opening for an outstanding individual interested in pursuing a PhD on neuromuscular and predictive modeling of motor adaptations during gait. The PhD project is funded through the SFI Center Insight.
Neuromuscular modelling of gait is useful for estimating unmeasurable physical quantities, such as muscle and joint forces or the activation of deep muscles, during the execution of the walking task.
Recently, Optimal Control problems applied to neuromuscular models have been used to predict motor behaviours based on specifically designed goals and constrains. This latter field is commonly referred to as predictive modelling. Predictive models are used to synthesize gait patterns when experimental data are not available, basing on high-level specifications, such as achieving a certain target speed while minimizing metabolic cost by applying optimization principles under physiological constrains.
The aim of this PhD project is that of developing predictive neuromuscular models able to explain the processes behind the adaptations in motor commands that occur during perturbed gait. Motor adaptation is the trial-by-trial alteration in motor commands that happens in response to a perturbation or to a modification in the movement environment. The proposed PhD project aims, through the development of predictive models of locomotor adaptations, at increasing our understanding of locomotor control in humans, with the aim of using this knowledge for developing novel training strategies for impaired individuals.
The PhD position is funded for 4 years and the start date for this position will be between September 2019 and January 2020.
Who Should Apply
Applicants should have, or expect to obtain before the beginning of the position, a first or upper second class honours Bachelors or Masters degree in Computer Science, Electrical, Electronic or Biomedical Engineering (or a related discipline). Suitable candidates will have a strong interest in modelling, biomedical engineering and computational neuroscience. Excellent analytical, computer programming (Matlab, Labview, C/C++…) and communications skills are essential. Self-motivation, an inquiring mind, ability to work independently are necessary for the position. Previous experience in neuromuscular modeling is a plus.
This position is funded by the SFI Insight Centre for Data Analytics (https://www.insight-centre.org/
). Studentship includes a tax-free stipend of €18,500 per year, coverage of tuition fees for EU students, funds for conference travel, and equipment allowance. The student will also have the opportunity to earn extra income through teaching activities.
How to Apply
Informal enquiries about this position can be made to: [email protected]
When applying, please use the same email address as above and subject "Applying PhD Position on neuromuscular and predictive modeling of motor adaptations during gait".
Strong candidates are requested to submit (in pdf format):
- 1 page cover letter detailing relevant experience and motivation behind the application
- Transcripts (courses with grades)
- Contact of two referees