Research Fellow (Health Data Science)
Salary: £40,977 - £45,508 per annum (Incl.LWA)
Department: School of Computer Science and Engineering
Location: University of Westminster, Central London
This post is full time, 35 hours per week and is fixed term until 30 June 2021.
Founded as Britain's first polytechnic in 1838, the University of Westminster has since developed into a university, which is closely involved in business, professional and academic life within London, as well as overseas.
With funding from the Quintin Hogg Trust and the Higher Education Innovation Fund, the University is putting significant investment into the development of the Health Innovation Ecosystem (HIE). The HIE is an innovative interdisciplinary programme to tackle global challenges in health, with ambition to become a hub for world leading research and knowledge exchange for innovation in health and wellbeing by 2022.
The Ecosystem focuses on huge issues facing the healthcare sector including; how do we define and measure health? What innovations can help people to lead healthier lives? How can we ensure more efficient hospital and primary care referrals? How do we measure and evaluate new interventions? How do we incorporate these into traditional health approaches in an effective and positive manner? How can technology, advanced analytics, data science, machine learning, new imaging technology and artificial intelligence help?
As a data scientist, you will have key role in the Health Innovation Ecosystem You will work on projects that require the development and use of data mining and machine learning algorithms to analyse patterns and make predictions (e.g. for screening, diagnosis, hospital admission, survival, etc.) based on large datasets such as the UK Biobank, the Hospital Episode Statistics, and other clinical or administrative datasets.
You are expected to hold a PhD in data science or a closely related area of computer science e.g. machine learning, artificial intelligence, operational research, and to have developed successful models using big datasets. You will have proven programming skills in a mathematical/statistical modelling language (preferably R) and in at least one programming language (preferably Python). You will have also a publication record in relevant areas of advanced analytics, data science or computer science. Previous involvement in writing research or consultancy bids is also desirable.
For more details including job description and person specification, and to apply for this vacancy, please visit this link.
Closing date: midnight on 2 May 2019
Interviews are likely to be held between 13 and 17 May 2019