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Research Associate

Imperial College London - National Heart & Lung Institute

Location: London, Hybrid
Salary: £49,017 to £57,472 per annum
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 19th November 2025
Closes: 16th December 2025
Job Ref: MED05514
 

About the role:

Join an interdisciplinary team of researchers from Imperial College London, A*STAR Singapore and the University of Manchester in applying advanced machine learning to transform how pulmonary hypertension is diagnosed and treated. The Research Associate will develop and apply probabilistic models to predict molecular and clinical trajectories from longitudinal patient data, working closely with clinicians, biologists, and data scientists across the UK and Singapore. This is an exciting opportunity to advance precision medicine through cutting-edge AI and translational research.

What you would be doing:

As a Research Associate in Machine Learning, you will play a key role in developing innovative AI models that uncover how molecular and clinical features of disease evolve over time. You will design and implement probabilistic frameworks—such as Gaussian Process models—to analyse complex, high-dimensional data from patient cohorts. Working closely with clinicians, biologists, and computational scientists across Imperial, Manchester, and A*STAR Singapore, your work will help translate molecular insights into predictive tools for precision health. You will also have the opportunity to publish in leading journals, present at international conferences, and shape the next generation of data-driven discovery in cardiopulmonary research.

What we are looking for:

  • A PhD (or near completion) in computer science, statistics, biomedical engineering, or a related discipline.

*Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant within the salary range £43,863 - £47,223 per annum

  • Strong experience in statistical modelling, probabilistic machine learning, or time-series analysis (e.g. Gaussian Processes, deep learning).
  • Proficiency in Python or R for data analysis and model development.
  • An understanding of molecular or clinical health data and enthusiasm for interdisciplinary research.
  • Excellent problem-solving, communication, and teamwork skills, with the ability to work effectively across computational and biological domains.
  • A proactive approach to research, with curiosity, creativity, and a commitment to producing high-quality, impactful science.

What we can offer you:

This role offers an excellent opportunity to contribute to a high-profile, interdisciplinary research programme at the interface of AI, medicine, and molecular biology. As part of this position, you will benefit from:

  • Working within Imperial’s National Heart and Lung Institute at the White City Campus, a leading cardiovascular centre for data-driven research.
  • Collaborating with world-class researchers across Imperial College London, the University of Manchester, and A*STAR Singapore.
  • Playing a central role in a UK Research and Innovation project pioneering machine learning models for longitudinal multi-omics and clinical data.
  • Gaining experience in translational research that bridges computational discovery and clinical application.
  • Opportunities to publish in high-impact journals, present at international conferences, and build your research profile.
  • Access to state-of-the-art computing facilities and a supportive, collaborative research environment that values professional growth and interdisciplinary training.
  • Sector-leading salary and remuneration package (including 39 days off a year)

Further Information

This is a full time, fixed-term role (12 months) with the possibility of extension. based on project progress and funding availability. This role is based at our White City Campus.

If you require any further details on the role, please contact: Dennis Wang dennis.wang@imperial.ac.uk

About Imperial

Welcome to Imperial, a global top ten university where scientific imagination leads to world-changing impact.

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