Research Assistant in Machine Learning for Clinical Trials

Imperial College London
London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior RF Data Scientist / Research Engineer

Senior Machine Learning Engineer

Principal, AI Data Science

AI Platform Engineer (DevOps / MLOps Focus)

Data Scientist - Supply Chain Optimisation

Computer Vision Engineer X 3

The Research Assistant will support the setup, management, and analysis of clinical trial datasets, applying machine learning methods to enhance study design, data quality, and health outcome modelling. Working closely with clinical and research teams, the role ensures robust data workflows and contributes to the development of analytical tools that strengthen our capacity to initiate and deliver new clinical studies. This dedicated post provides continuity and technical expertise for ongoing and future clinical research programmes.


You will support the setup, curation, and analysis of clinical trial datasets, applying statistical and probabilistic modelling, and machine learning methods to extract high-quality insights that inform study design and clinical outcomes. Working closely with clinicians and researchers, you will develop reproducible data pipelines, perform statistical and ML modelling, and contribute to interpreting results that guide ongoing and future trials. You will also help establish robust data workflows and study designs that strengthen our capacity to launch and deliver new clinical studies.


We are looking for a highly motivated researcher with an MSc in biosciences, neuroscience, computer science, or a closely related discipline, and a solid grounding in clinical studies, as well as expertise in research methods and statistical analysis. You should bring practical experience in a research environment, a track record of high-quality publications in international peer-reviewed journals, and the ability to organise your work independently while contributing effectively to a collaborative team. We value creative problem-solving, scientific curiosity, and the ability to drive high-quality research in a fast-moving clinical and data-science setting.


A highly collaborative, multidisciplinary research environment working at the forefront of machine learning for healthcare, including projects on dementia care, digital health, EHR analytics, generative models, and time‑series modelling. 
Opportunities to contribute to impactful clinical and translational research, with access to real-world clinical datasets, cutting-edge tools, and active collaborations across engineering, medicine, and AI. 
Training, mentorship, and career development within a supportive team, including involvement in publications and conference presentations.
The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity.
Grow your career: gain access to Imperial’s sector-leading as well as opportunities for promotion and progression.
Sector-leading salary and remuneration package (including 41 days off a year and generous pension schemes).
Be part of a diverse, inclusive and collaborative work culture with various and resources to support your personal and professional .

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.

New AI Employers to Watch in 2026: UK and Global Companies Reshaping AI Careers

The artificial intelligence job market in the UK is evolving at an extraordinary pace. With record-breaking investment, government backing, and a surge in enterprise adoption, the landscape of AI employers is shifting rapidly. For candidates exploring opportunities on ArtificialIntelligenceJobs.co.uk, understanding who is hiring next is just as important as understanding what skills are in demand. In this article, we explore the new and emerging AI employers to watch in 2026, focusing on organisations that have recently secured funding, won major contracts, or expanded their UK footprint. From cutting-edge startups to global giants doubling down on Britain, these companies represent the next wave of AI career opportunities.

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.