Research Assistant/Research Fellow in Cancer Epidemiology / Data Science

UCL Eastman Dental Institute
London
10 months ago
Applications closed

Related Jobs

View all jobs

Data scientist (IT) level 6 apprentice - Immunocore Immunocore

Research Fellow in Machine Learning for Hydroclimatology

Research Fellow in Machine Learning for Hydroclimatology

Research Assistant/Associate in Cardiac Computational Modelling via Machine Learning and Biomechanics Simulations

Postdoctoral Research Assistant in Health Data Sciences

Postdoc in Optical Neural Networks & Deep Optics

About the role

The post holder will work closely with members of the ECHO Group to define, curate and analyse healthcare data of relevance to diagnostic and treatment care pathways and outcomes for cancer patients. Within a range of analytical projects that require statistical analysis or data science leadership, the post-holder will be defining new answerable research questions in synergy with the overall post objectives and programmatic commitments, including risk stratification and understanding variations in intervals and pathways to the diagnosis of cancer.

Application Details

This is an open-ended contract with fixed-term funding until 31st of December in the first instance. Appointment at Grade 7 is dependent on award and confirmation of a PhD (or equivalent). If this is not the case, initial appointment will be at Research Assistant Grade 6B, point 28 (salary £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. This role meets the eligibility requirements for a skilled worker certificate of sponsorship or a global talent visa under UK Visas and Immigration legislation. Therefore, UCL welcomes applications from international applicants who require a visa.

Application Process 

A full job description and person specification can be accessed at the bottom of this page. Please use the personal statement section to explain how you meet each of the essential and desirable criteria outlined in the person specification.

Contact Details 

If you have any queries regarding the vacancy or the application process, please contact DrMeena Rafiq () or Prof Georgios Lyratzopoulos () If you need reasonable adjustments or a more accessible format to apply for this job online or have any queries about the application process, please contact 

About you

Experience of prior healthcare epidemiology / data analysis work in academic research departments or service environments ( NHS Digital, CPRD, Public Health England), or relevant sectors of the health industry is desirable, particularly regarding the use of person-level electronic health records and administrative population-based data. Applicants must have relevant work experience and be competent in using command-line interface statistical software. Inquiries from interested applicants are encouraged.

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 and expenses Relocation scheme for certain posts On-Site nursery On-site gym Enhanced maternity, paternity and adoption pay Employee assistance programme: Staff Support Service Discounted medical insurance

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.