Multi-sensor and AI enabled system design for remote monitoring of physiological signals and activities in COVID-19 imposed conditions

Eligibility: UK/EU graduates with the required entry requirements

Reason for eligibility restriction: Funder requirement and timescale

Duration: Full-Time – between three and three and a half years fixed term

Application deadline: 14th August 2020

Interview date: Will be confirmed to shortlisted candidates

Start date:  September 2020 or January 2021. Entry point will be subject to discussion and agreement.

For further details contact: Dr Sara Sharifzadeh 


Coventry University (CU) is inviting applications from suitably-qualified graduates for a fully funded PhD studentship in Artificial Intelligence and Signal Processing domain.

Coventry University has been voted ‘Modern University of the Year’ three times running by The Times/Sunday Times Good University Guide. Ranked in the UK’s top 15 (Guardian University Guide), we have a global reputation for high quality teaching and research with impact. Almost two-thirds (61%) of our research was judged ‘world leading’ or ‘internationally excellent’ in the Research Excellence Framework (REF) 2014.

The Research Centre for Data Science (CDS) aims to develop cutting edge pure research in Artificial Intelligence, Data Science and Future Computing, linking fundamental science to real-world applications.

Data Science deals with the analysis and exploitation of large amounts of data (Big Data) drawing together disciplines as diverse as Computer Science, Artificial Intelligence, Statistics and Mathematics. The centre is organised according to three key themes:

  • Machine Learning for Big Data
  • Wireless Sensors and Internet of Things
  • Computational and Statistical Modelling
  • Advanced Computing

About the project

The COVID-19 pandemic has infected more than 5 million people worldwide. The elderly and those with chronic disease or suppressed immune systems are among the most vulnerable, facing issues related to their health and life condition.

This project is about developing a smart IoT-based multi-sensor system. The aim is to adopt sensor technology and AI techniques, to design a smart Internet of Things (IoT) system for remote detection of the physiological and physical status of an individual as indicators of health and normal life condition and identify risk condition, e.g. a fall and breathe shortage, in daily life. The project has three objectives:

  1. To develop a multi-sensor system for acquiring signal/image from a human body remotely.
  2. To train ML/AI models from the heterogeneous datasets to interpret the health condition and identify risk scenarios.
  3. To utilise the results for the optimum selection of sensor settings and produce design guidelines.

The system can assist in independent living of the aged population with mobility capabilities that demand continuous health checks. This can reduce the pressure on the health care providers during pandemics, and minimise the infection and death rates among the elderly, helping them gain long-term independent living.

Funding details

Full studentship which includes tuition fees and stipend for a doctoral candidate over 3.5 years.


Considering the induced challenges by the COVID19 condition and the high demand for clinical care, this project is addressing an important problem in assistive healthcare for independent living.  The results of this project allows further understanding of smart caring systems requirements including the multi-sensor system design and data analysis perspectives. The results of this project has great impact and helps the stakeholders such as NHS, care homes and the housing companies to utilise the project findings such as system design and AI algorithms.

On the other hand, employing and developing multi-sensor data acquisition system and AI techniques, strengthens the candidate skills and support the candidate for future career.

Coventry University will benefit from this cutting-edge research project by generating three journal publications in high-impact journals, e.g. Elsevier and IEEE Transactions. This will helps the University to meet its target in the UK Research Excellence Framework (REF) also improve its position globally.

  • Our research strategy is underpinned by a £250m investment in research and facilities
  • Dedicated Doctoral College and Centre for Research Capability Development deliver high quality professional support for researchers, from PhD to Professor
  • Free training: research career planning, managing your doctorate, research communication skills, research ethics, research impact, research integrity, research methods and research supervision
  • Coventry is a member of the Doctoral Training Alliance (DTA), the largest multi-partner and only nationwide doctoral training initiative of its kind.

The successful candidate will receive comprehensive research training including technical, personal and professional skills. All researchers at Coventry University (from PhD to Professor) are part of the Doctoral College and Centre for Research Capability and Development, which provides support with high-quality training and career development activities.

Entry requirements

  • A minimum of a 2:1 first degree in a relevant discipline/subject area with a minimum 60% mark in the project element or equivalent with a minimum 60% overall module average. 


  • In the event of a first degree classification of less than 2:1, a Masters degree in a relevant subject area will be considered as an equivalent. The Masters must have been attained with overall marks at minimum merit level (60%). In addition, the dissertation or equivalent element in the Masters must also have been attained with a mark at minimum merit level (60%).
  • A taught Masters degree in a relevant discipline, involving a dissertation of standard length written in English in the relevant subject area with a minimum of a merit profile: 60% overall module average and a minimum of a 60% dissertation mark


  • the potential to engage in innovative research and to complete the PhD within a 3.5 years
  • a minimum of English language proficiency (IELTS overall minimum score of 7.0 with a minimum of 6.5 in each component)
  • A good knowledge of linear algebra, machine learning and AI concepts, linear/non-linear systems, and willingness to quickly learn further in this area
  • Digital sensors data acquisition, experimental, modelling and analytical experience related to multimodal signals
  • Good programming skills in MATLAB/Python
  • Good writing and interpersonal/communication skills

How to apply

All applications require full supporting documentation, a covering letter, plus a 2000-word supporting statement showing how the applicant’s expertise and interests are relevant to the project.

Apply to Coventry University