Research Fellow in Machine Learning for Multi-scale, Correlative, Biomedical Imaging

UCL Eastman Dental Institute
London
1 year ago
Applications closed

Related Jobs

View all jobs

Research Fellow in Applied Machine Learning

Senior Scientist - Data Science for Simulation

Technical Program Manager - Machine Learning - New York

Computer Vision and Artificial Intelligence Engineer

Reader in Artificial Intelligence (Machine Learning, NLP, Reinforcement Learning, and AI Security)

Reader in Artificial Intelligence

About the role

Do you want to work in a team integrated cutting edge imaging and spatial transcriptomics of the human heart with state-of-the-art ML models to? We are looking for a Post-doctoral Research Fellow with an image analysis/Machine Learning (ML) background to work at integrating correlative high resolution 3D X-ray imaging and Spatial Transcriptomics. You will be based at University College London developing ML based piplines to i) segment 3D tissue strucutres from Hierarchical Phase-Contrast Tomography (HiP-CT) data (see , ii) use these structures as a base line to perform registration between 3D HiP-CT, 2D histological sections and spatial transcriptomic. You will collaborate closely with the project team at Cambridge where spatial transciptomic data is being acquired and with collegues at the European Synchrotron (ESRF) in France where HiP-CT scans are performed.. This post is funded for 2 years in the first instance, with the possibility of extension. A job description and person specification can be accessed at the bottom of this page. If you wish to discuss the post informally, please contact Claire Walsh ( ) or for application process queries Ruikang Xue ().

About you

The post will require a motivated researcher with experience in machine learning for segmentation and image registration. You will have a PhD and extensive knowledge and expertise in a relevant field. It is desirable to have experience in handling large imaging data. Your expertise should be at a level appropriate for the conduct of research and publishing new knowledge in leading international research journals. The post-holder will need to show a high level of initiative and an ability to work collaboratively and independently. Applicants should have good team-working skills and a strong command of English. You will join a dynamic international multidisciplinary group of academics, clinicians, beamline scientists, post-docs and PhD students developing and applying synchrotron X-ray and other techniques to study biological systems. You will report to Dr Claire Walsh & Prof. Peter Lee at UCL.

What we offer

For information about our rewards and benefits please visit

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.

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.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.