About the role
This research role is on the project PREDICT – which brings together clinicians and data scientists from Barts Health and Barts Life Sciences, natural language processing specialists Clinithink, and experts in urban analytics from University College London. Barts aims to reduce life-threatening illnesses caused by undiagnosed heart valve disease, to redress health inequalities and to reduce the suffering and costs of heart valve disease through earlier detection. Bart’s NHS Trust is developing a community-facing service for heart tests, which need to be better targeted. The main research task of the UCL team will be working on the work packages, , Social Geography Mapping of NE London Valvular Risk and better detection of valve diseases. The role requires close work with academics at the Centre of Advanced Spatial Analysis (Dr Chen Zhong) and the Department of Geography (Dr Stephen Law) at UCL and with industrial partners from Barts. Duties and responsibilities will include: Review the latest literature on the health population and in particular, data-driven and machine-learning methods applied to improve health services; Construct a semantically enriched social and environmental health determinants database, gathering data from open sources and integrating it with clinical data from Barts; Constructing spatial regression and machine learning models (or other models) to predict patients at risk of undiagnosed heart valve disease; Visualising the outcomes through geographical mapping; Assisting Barts’s research team in exploring multi-modal data science approaches to establish culturally appropriate community diagnostic hubs; The role requires good communication skills with academics, clinic and non-clinic staff and potentially the public; Participate in meetings with UCL colleagues on research and project progress, and in meetings with the wider project consortium; Write academic papers for conferences and journal publications in collaboration with UCL and Barts’s colleagues; Share academic outputs through project presentations, conferences, and any public engagement events; Adhere to guidelines on research ethics, data security, storage and protection.The post is available from 1 July and is funded until 30 June in the first instance. Starting salary offered will be in the range of £43,- £49, per annum, inclusive of London Allowance, due to limited amount of funding available. Appointment at Grade 7 is dependent upon having been awarded a PhD; if this is not the case, initial appointment will be at Research Assistant Grade 6B (salary - £38,–£41, per annum, inclusive of London Allowance) with payment at Grade 7 being backdated to the date of final submission of the PhD thesis. This appointment is subject to UCL Terms and Conditions of Service for Research and Professional Services Staff. Please visit for more information. We will consider applications to work on a part-time, flexible and job share basis wherever possible. For any queries about the role please contact Chen Zhong (). A job description and person specification can be accessed at the bottom of this page. To apply for the vacancy please click on the ‘Apply Now’ button below.
About you
The postholder will have a PhD degree (or soon to complete) in a relevant discipline, for example, geography, GIS, spatial data science, computer science, engineering. Appointment at Grade 7 requires a completed PhD in a relevant discipline. Other essential criteria include: Knowledge of a programming language for reproducible spatial data analysis and modelling ( Python, R); Good knowledge of research challenges in health geography; Familiarity with geographic data sets and ability to manipulate, analyse, and visualise this data in relation to accessibility, spatial inequality, and spatial organisation; Excellent understanding in applying spatial data science methods, , spatial clustering, regression, optimisation and machine learning methods; Ability to design and conduct quantitative research in the field of urban geography, and health geography; Ability to communicate the research with people from diverse background; Proven ability to write up research findings in the form of peer reviewed journal publications and/or conference proceedings; A positive and flexible attitude with a willingness to take on new areas of application and to contribute to the development of the research; Good reliability, motivation and organisational skills in the workplace, able to manage a varied workload whilst still being able to meet deadlines and displaying evidence of the ability to complete tasks and projects to a high standard with limited supervision. For full list of essential and desirable criteria, please see a job description and person specification at the bottom of this page.
What we offer
As well as the exciting opportunities this role presents, we also offer some great benefits some of which are below: - 41 Days holiday (27 days annual leave 8 bank holiday and 6 closure days); - Additional 5 days’ annual leave purchase scheme; - Defined benefit career average revalued earnings pension scheme (CARE); - Cycle to work scheme and season ticket loan; - Immigration loan Relocation scheme for certain posts; - On-Site nursery; - Onsite gym; - Enhanced maternity, paternity and adoption pay; - Employee assistance programme: Staff Support Service; - Discounted medical insurance.