Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Research Assistant/Research Fellow in Cancer Epidemiology / Data Science

UCL Eastman Dental Institute
London
6 months ago
Applications closed

Related Jobs

View all jobs

Research Assistant/Research Fellow in Cancer Healthcare Epidemiology / Data Science

Research Assistant / Research Fellow in Epidemiology/Data Science

Postdoctoral Data Scientist Engineer for the Quantitative Neuroradiology Initiative

Postdoctoral Data Scientist Engineer for the Quantitative Neuroradiology Initiative

Machine Learning Engineer

Machine Learning Engineering Lead

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.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.

AI Team Structures Explained: Who Does What in a Modern AI Department

Artificial Intelligence (AI) and Machine Learning (ML) are no longer confined to research labs and tech giants. In the UK, organisations from healthcare and finance to retail and logistics are adopting AI to solve problems, automate processes, and create new products. With this growth comes the need for well-structured teams. But what does an AI department actually look like? Who does what? And how do all the moving parts come together to deliver business value? In this guide, we’ll explain modern AI team structures, break down the responsibilities of each role, explore how teams differ in startups versus enterprises, and highlight what UK employers are looking for. Whether you’re an applicant or an employer, this article will help you understand the anatomy of a successful AI department.