Teaching, Research & Scholarship
Fixed term contract
Fixed Term Duration
Faculty of Business & Law
Anglia Ruskin is a vibrant workplace and our University is recognised both
nationally and internationally. We have ambitious plans for the future and we
are determined that our students and staff will realise their full potential.
Our main campuses in the cities of Cambridge, Chelmsford, London and
Peterborough have been transformed with major capital investment. With an
annual turnover of over £200m, we are a major force for higher education and
one of the largest universities in the East of England.
About the role:
Data collected from wearable devices and the Internet of Things system can be
utilised to create intelligently expanded end user healthcare portfolios.
Analytics are required to extract relevant information from the large amount
of complex data, and to translate this information into useful insights to
assist decision making regarding diet, lifestyle and physical exercise.
The project aims to promote healthy lifestyles and help improve the general
state of health and wellbeing of the UK population. This project will collect
health and wellbeing data from multiple sources, including wearable devices,
interviews and self-reporting from Patient and Public Involvement (PPI)
groups, social media platforms, and databases such as UK Data Service. These
data will be analysed to monitor individuals' history of illness, lifestyle
parameters, mental and psychological parameters, socioeconomic parameters,
gender parameters, contextual parameters (work, location, etc.) and cultural
parameters. Applying machine learning and advanced data analytics to the
collected data, we could create digital twins of individuals. The digital
twins have several functionalities: 1) The digital twins produce wellbeing
profiles for the individuals, associating indicators with well- and ill-being.
The profiles enable identification, comparison and monitoring trends among
interviewed people. 2) The digital twins identify factors leading to ill-
being and their causal links. 3) The digital twins feed the collected data
into the machine learning models to experiment intervention, and to test
effectiveness of personalised healthy living advice, including healthy eating,
work/life balance, physical activity plan, etc.
The outcome of this research will change the way we engage in eating, working
and physical activity. It will also deliver personalised healthy eating,
working and living advice to the public.
The candidate will have or expect to achieve d a postgraduate
(Distinction) or equivalent in Computer Science, Engineering, Data
Science, Statistics, Math, or a broad range of relevant backgrounds in
Science / Engineering degree.
Having experiences and knowledge of machine learning, data mining, and
Having strong mathematical or statistical background, with the ability to
construct modelling and simulation
Having strong programming skills using R or Python
Having experience or ability of collecting data from multiple resources,
including interviews with PPIs
Demonstrating ability of using SQL or other databases to store,
manipulate, sort and make queries of data.
Having strong communication and writing skills in English
Demonstrating confidence in communicating and collaborating with
Being self-motivated and having a strong interest in doing research
It is desirable that the candidate has a good understanding on healthy
living and wellbeing profile.
Applicants must meet English language requirements, and the project expects an
IELTS of 6.5 in order to be accepted for the PhD programme. Read more here.
The successful candidate will be responsible for collecting data to create
Digital Twins of real-world environments. The successful applicant will work
closely with the research centres in Faculty of Business Law, including the
Anglia Ruskin Innovation Centre with The Welding Institute, and Centre for
Intelligent Supply Chain. The PhD candidate will be supervised by Prof. Ying
Xie from Faculty of Business and Law, Anglia Ruskin University, and Prof.
Barbara Pierscionek from Faculty of Healthcare, Education, Medicine and
Social Care, Anglia Ruskin University. Ocado Technology will be the
industrial partner of this project, to supervise the design, execution and
analysis of digital twins' models, in collaboration with academic supervisors.
Ocado Technology will also advise the PhD student and academic supervisors on
feasibility of digital twins in practice.
Applicants must be prepared to study on a full-time basis, attending at our
Cambridge or Chelmsford campus, subject to UK Government Covid-19 movement
How to apply:
Applications for the PhD Scholarship are made here. Please choose the course
title “PhD with progression from MPhil School of Economics, Finance and Law”,
Full Time, ARU Chelmsford Campus, R0177FCHE02D, 18/Jan/2022.
In addition to the online application, please send the following documents to
email@example.com and firstname.lastname@example.org . Please ensure that
you make a note of the project title.
Certificates and transcripts from your postgraduate degrees
Your personal statement explaining your suitability for the project
Passport and visa or EU Settlement Scheme share code (if applicable)
Two reference letters
For further information, please contact Prof. Ying Xie via email@example.com
We will review all applications after the submission deadline of 24 th
October 2021. We will contact shortlisted applicants in the week commencing
1 st November 2021. Interviews will be held in the week commencing 8 th
Find out more about working with us.
We offer an extensive range of benefits including a generous holiday
entitlement, occupational pension schemes, training and development
opportunities, travel to work scheme and a competitive relocation package.
Visit our benefits page for full details.
We value diversity at ARU and welcome applications from all sections of the
Committed to being inclusive and open to discuss flexible working.