Lecturer (Teaching) in Health Data Science or Health Care Artificial Intelligence (Maternity Cover)

UCL Eastman Dental Institute
London
3 months ago
Applications closed

Related Jobs

View all jobs

Lecturer in Artificial Intelligence Education (AEP) x2

Lecturer in Artificial Intelligence Education (Programme & Software Development (Academic Education

Lecturer in Artificial Intelligence (2 roles)

Lecturer/Senior Lecturer in Artificial Intelligence

Lecturer / Senior Lecturer in Artificial Intelligence

Lecturer in Artificial Intelligence Education (Programme & Software Development)(Academic Education Pathway)

About the role

We’re looking for a Lecturer (Teaching) to join our team and help shape the future of health informatics. You’ll play a key role in carrying out high quality research particularly where the scale or detail of data allows scientific advances of relevance to decision makers.


A full list of responsibilities can be found on the attached job description


This is a full-time post ( hours/week), for 12 months.


For informal enquiries, please contact Johan Thygesen at


For questions about the recruitment process, contact Anita Gorasia at

About you

If you believe you meet the requirements, come and be part of this unique and exciting opportunity and contribute to our mission to improve health outcomes through research.


You’ll have:

A PhD in a relevant discipline


Experience of teaching statistics, epidemiology, health data science or related subjects in a higher education setting, preferably at MSc level
Ability to supervise postgraduate research
Advanced statistical skills in at least one statistical programming language/software package (;R or Stata)
Experience of and enthusiasm for collaborative and team-based working

Your application must include a CV and a supporting statement and it will be assessed on how you evidence the essential and desirable criteria in the job description. Please see the attached job description and person specification for more information.

What we offer

At UCL, we believe work should fit around life – not the other way around. That’s why we offer flexible working options, including part-time roles and job-sharing opportunities wherever possible.


But it’s not just about flexibility – it’s about feeling rewarded, too.


When you join UCL, you’ll enjoy:

41 days of holiday (pro rata for part-time staff) – that’s 27 days of annual leave, 8 bank holidays, and 6 closure days


Cycle to work scheme – save money and stay healthy
Season ticket loan – making your commute more affordable
On-site gym – fitness made convenient
Employee Assistance Programme – for confidential wellbeing support when you need it

Whether you're looking to grow your career or simply find a better balance, UCL could be the right place for you.


Learn more about our full range of benefits at:

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

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.