About the Project
Eligibility: Home/EU and International Students
Bursary: £14,057 per annum for three years for a stipend, £3,300 for project costs
Fees: Tuition fees will be paid by the University
Deadline: 24 October 2018
Start date: 21 January 2019
The Faculty of Technology, Design and Environment at Oxford Brookes University is pleased to offer a three-year, full-time PhD studentship to a new student commencing in January 2019.
The successful candidate will work under the supervision of Dr Tjeerd olde Scheper in the School of Engineering, Computing and Mathematics in collaboration with Prof Helen Dawes in the Department of Sport, Health Sciences and Social Work.
Brief project description:
Analysis of biological data is based around the interpretation of data within the context of its source. Gait, as primary motive means for humans, is both energetically demanding, and reflects many of the human disorders. Physical disorders (muscle atrophy, etc.), mental disorders (Alzheimers, Parkinsons, etc.), as well as energetic dysfunction (diabetes, malnutrition, etc.) are readily expressed in gait. However, the underlying complexity prevents easy analysis, because of the intricate nonlinear relations involved in the biosystems that allow effective gait. Criticality Analysis (CA) makes it feasible that biological information can be extracted from intricate systems. CA is based on the proven method of Rate Control of Chaos (RCC), and provides a means of generating nonlinear representation spaces based on dynamic interaction, rather than probabilistic models.
The key research questions are (not exclusive):
1. Determine the critical parameters, based on already shown results, that allow a critical system to reflect the data accurately;
2. Investigate the numerical properties of the data representation, based on different controlled models, and connectivities of the underlying network;
3. Create a representative model system that can analyse gait data for specific disorders, and determine the boundary conditions for reliable and effective categorisation and identification.
Requirements:
We are looking to recruit a highly accomplished candidate, capable of submitting a PhD thesis
within the 3 years of the project. Candidates would be expected to have a good first degree, or Masters, in a related subject (e.g. mathematics, computer science with data analysis, physics, computational biology, etc.). They should be able to demonstrate strong research capabilities, and proficiency in spoken and written English. Required skills are mathematical understanding of dynamic systems, scientific modelling, and software engineering. Desired skills are biological data analysis, and statistical analysis.
Competence to develop:
The successful candidate may expect to work in a developing research group in machine learning. They will develop skills in data analysis, computational research, scientific methods, and machine learning.
Enquiries: Please email Dr Tjeerd olde Scheper – [Email Address Removed].
As part of the application, you must submit a detailed research proposal (maximum 1000 words), a
CV, and a supporting statement (maximum 300 words).
How to apply: For further information on how to apply, please email [Email Address Removed]
for an application pack, quoting “Criticality Gait Analysis” in the subject line.
Funding Notes
Bursary: £14,057 per annum for three years for a stipend, £3,300 for project costs
Fees: Tuition fees will be paid by the University
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