Connectionists: Fully funded PhD position on ECG-Derived Biosignals

[Herzallah, Randa]

Fully funded PhD studentship in Aston University, UK

http://www.jobs.ac.uk/job/ANN825/ecg-derived-biosignals/<https://jobs.aston.ac.uk/Vacancy.aspx?ref=R160152>


Applications are invited for a three year Postgraduate studentship, supported by the School of Engineering and Applied Science, to be undertaken within the Non-linearity and Complexity Research Group<http://www.aston.ac.uk/eas/research/groups/ncrg/> at Aston University. The successful applicant will join an established experimental group working on signal processing and probabilistic modelling and control of complex dynamical systems. The studentship is offered in collaboration with Isansys Ltd<http://www.isansys.com/>, Oxford.

The position is available to start in October 2016 (subject to negotiation)

Financial Support
This studentship includes a fee bursary to cover the home/EU fees rate plus a maintenance allowance (£14,296 in 2016/17).

Applicants from outside the EU may apply for this studentship but will need to pay the difference between the ‘Home/EU’ and the ‘Overseas’ tuition fees (approximately £12,000 per annum). Confirmation that this additional funding support is in place will be required as part of the application process.

Background of the Project
In collaboration with Isansys Ltd<http://www.isansys.com/>, Oxford, this project will focus on detailed linear and nonlinear signal processing of biomedical time series derived directly from low-level sensor data. The intention is to reliably and robustly extract physiological parameters linked to raw electrocardiogram signals which would be beneficial for monitoring, prognostic prediction and advisory decision support in a clinical environment. Current approaches for extracting physiological parameters such as breathing rate, heart rate variability and other novel indicators of well-being such as the effort of breathing and signal complexity for example, will be developed to work with a full age range of patients in a hospital situation. Predictive modelling approaches in this nonstationary and uncertain environment using such indicators will be researched towards improving the capability to forewarn of impending patient distress.

Person Specification
The successful applicant should have a first class or upper second class honours degree or equivalent qualification in areas such as Electronic & Electrical Engineering, Applied Mathematics, Applied Physics or Biomedical Engineering. Preferred skill requirements include knowledge/experience of signal processing, filters, machine learning, time series methodologies, data mining and computational analysis.

We would particularly like to encourage applications from women seeking to progress their academic careers. Aston University is committed to the principles of the Athena SWAN Charter<http://www.ecu.ac.uk/equality-charter-marks/athena-swan/>, recognised recently by a prestigious Silver Award to EAS, and we pride ourselves on our vibrant, friendly and supportive working environment and family atmosphere.

For informal enquiries about this project and other opportunities within the Non-linearity and Complexity Research Group, contact Randa Herzallah by email r.herzallah at aston.ac.uk<mailto:r.herzallah at aston.ac.uk> or David Lowe d.lowe at aston.ac.uk

The online application form, reference forms and details of entry requirements, including English language are available here<http://www1.aston.ac.uk/eas/research/prospective-research-students/how-to-apply/>.

Applications must also be accompanied by a short research proposal including a brief relevant literature review linked to this project, and explaining how your knowledge and experience will benefit the project.

____________________________________________
Dr Randa Herzallah
Non-linearity and Complexity Research Group
Aston University
Aston Triangle
Birmingham, B4 7ET
UK
tel: +44 121 204 3533
fax: +44 121 204 3685
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