Research Fellow in Spatial Data Science (Public Health)

UCL Eastman Dental Institute
London
2 weeks ago
Create job alert

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.

Related Jobs

View all jobs

Senior UX Visual Design Specialist

Junior Data Scientist

Senior Data Analyst

Research and Insight Executive

Research Manager (Education)

Research Manager (Brand Design)

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.