Research Associate in AI and Machine Learning

Imperial College London
London
10 months ago
Applications closed

Related Jobs

View all jobs

Data Engineering Associate Director

Data Engineering Associate Director

Data Engineer

Data Engineer

Python Data Engineer - Hedgefund

Benefits & HR Systems Data Analyst

Developing artificial intelligence-enabled electrocardiograms and intracardiac electrograms

Applications are invited for the position of post-doctoral research associate, to work at the National Heart and Lung Institute, Imperial College London. We are a multi-disciplinary team seeking a highly motivated post-doctoral research associate to join a collaborative team of clinicians, basic scientists, and physical scientists working on cardiovascular research, currently funded by a British Heart Foundation Programme Grant. The present post is funded by a UKRI Impact Accelerator Award and an NIHR Biomedical Research Centre grant, both

focused on developing new artificial intelligence (AI) models to apply to electrophysiological signals, in the form of electrocardiograms (ECG) and intracardiac electrograms (EGM).

Through various collaborators worldwide, we have access to large quantities of digital ECGs (>2 million) recorded in clinical settings, in addition to >60000 digital ECGs from the UK Biobank linked to genetic and phenotypic data, which will allow us to train a range of AI-ECG models. We also have access to a large database of intracardiac EGM data collected during invasive catheter ablation procedures, and from collaborators in industry.

The post-doctoral research associate will work with other members of the team to use these datasets to develop new AI-ECG models and AI-EGM models for cardiovascular risk and mortality prediction, and for diagnostic classification tasks, building on our group’s recent success


The post-doctoral research associate will develop new AI-ECG models and AI-EGM models for cardiovascular risk and mortality prediction, and for diagnostic classification tasks. The post holder will work closely with the clinicians, biologists, bioengineers and physical scientists within the multi-disciplinary group


You should have a PhD (or submitted a PhD and awaiting viva), or an equivalent qualification, industrial or commercial experience, in a computational discipline.

*Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant within the salary range £43,003 - £46,297 per annum

Experience in computer programming (in particular Python), is essential, and previous experience with AI research is highly desirable.  A background in cardiovascular research is also desirable. You should also have a collaborative approach to research as this role requires working with other groups both within and outside the department. 


Supporting you in developing your career into an independent researcher The opportunity to continue your career at a world-leading institution Sector-leading salary and remuneration package

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.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.