Two fully funded PhD posts available @DerbyUni with @profpaulstewart applying control engineering and AI to MedTech

#iTrend project members at the last data workshop.
L-R Prof Maarten Taal, Prof Jill Stewart, Dr Tarek Eldenhi, Prof Paul Stewart, Dr Latha Gallapudi, Dr Nick Selby

The fully funded studentships will carry out research to support the iTrend (Intelligent Technologies in Renal Dialysis) project team, which is a collaborative research project between the Derby University, Royal Derby Hospital and Nottingham University.

School of Engineering and Technology, University of Derby

Two funded full-time traditional route PhD Post Graduate Research Assistantship (PGRA) studentships are available to supplement the research team working on the ITrend (Intelligent Technologies for Renal Dialysis) programme. The studentships covers tuition fee to the UK home/EU level and provide a tax-free stipend of £18,777 pa for 3 years subject to satisfactory progress. The start date is January 2019 or the next available intake.

  1. ‘Machine learning, automatic modelling and control system identification in complex physiological systems’
  2. ‘Intelligent analytics and control for data-driven connected IoT networks’


Qualification type: PhD
Location: Derby, UK
Funding amount: £18,777 stipend pa + UK home tuition fees
Hours: Full Time
Closes: 10 January 2018
Interview: 17 January
Start date: January 2019

The students’ activities will be associated with the iTrend research programme. The programme is a collaborative project between the Universities of Derby and Nottingham and Derby Royal Hospital. The project is funded by the MStart Charity and is led by Principal Investigator Prof Paul Stewart.

The aim of the project is to improve the outcome for patients with end-stage renal failure who depend on hemodialysis treatment. To support this activity, the RDH is conducting a 50-patient study collecting real-time physiological data while the patients receive treatment, a first in the analysis of renal failure treatment.

The data from the project forms a large, unique repository, maintained and analysed by Prof Jill Stewart. In parallel with this, an experimental cardiovascular system is now built and running in the programme laboratory in Lonsdale House.

Project 1

Machine learning, automatic modelling and control system identification in complex physiological systems

This PhD will bridge the gap between the data repository and the experimental programme. In particular, the student will apply evolutionary machine learning techniques to identify individualised models of the patients’ baroreflex (autonomous nervous system control of heart and peripheral blood system maintained by the nervous system).

The models developed will allow simulation of individuals and associated effects of hemodialysis on them, as well as giving a novel and unique ‘fingerprint’ to identify physical degradation due to the treatment and progression of disease.

Project 2

Intelligent analytics and control for data-driven connected IoT networks

The PhD will investigate and develop new methods and hardware to enable the creation of smart, intelligent healthcare sensor networks for personalised treatment. The project will develop hardware and sensor networks to support timely and accurate diagnosis, stratification, predictive modelling and real-time evidence-based decision making.

In particular, the project will design novel strategies to predict physiological degradation of the nervous system and cardiovascular response in renal dialysis patients with a portal to individual treatment delivery.

Entry Requirements

Previous technical research experience is required, either at Masters level or as strong component of independent project work at Bachelor’s level. Prior experience with real-time control, data analysis and experimental electronics and control laboratory work is essential. We welcome applications both from candidates with a first degree in an Engineering of Physics-related subject, with a strong interest in computing and from candidates with a first degree in a computing-related subject with an interest in working with real-time data and control.

How to apply:

In order to apply, please see the University website at In addition to the documents requested on the website, please also include with your application a Curriculum Vitae and a covering letter. Completed applications should be submitted by email to, quoting reference iTrend_studentships_pgra_0119 in the subject line.

For further information and informal discussions on possible research topics please contact Professor Paul Stewart( Please note that applications sent directly to this email address will not be accepted. If you have not been invited for interview by the interview date, please assume that on this occasion your application has not been successful.

These Studentship positions are only available to UK/EU applicants. If your application is successful and you are assessed as Overseas for fees purposes, you will need to pay the difference between the Home/EU fees and the Overseas fees.

About Paul Stewart 301 Articles
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