Research Associate in Deep Generative Modelling for Infectious Diseases
About the role
Are you a machine learning researcher with expertise in deep generative modelling, eager to apply your methods to some of the most pressing challenges in global health? We are looking for a Research Associate to lead methodological development at the interface of deep learning and infectious disease modelling, working within a highly collaborative international team at Imperial College London.
What you would be doing
You will drive forward methods research in deep generative modelling, simulation-based inference, and neural approaches to spatial and spatiotemporal Bayesian inference. Your work will focus on developing principled, scalable tools, including deep generative modelling and neural surrogate models, that address fundamental computational challenges in fitting complex disease models to data. You will have significant freedom to pursue rigorous methodological innovation, with validation and application grounded in the real scientific problem of antimalarial drug resistance in sub-Saharan Africa.
What we are looking for
- A PhD in machine learning, statistics, applied mathematics, computer science, or a closely related quantitative discipline.
- Demonstrated research experience in deep learning and probabilistic machine learning, evidenced by publications, preprints, or open-source contributions.
- Practical experience designing, training, and evaluating deep generative models.
- Strong programming skills in Python, with proficiency in PyTorch or JAX.
- Ability to develop and adapt methods for novel scientific applications, and to communicate them clearly across disciplinary boundaries.
- Being proactive at exploring new research ideas, incusing due diligence.
What we can offer you
- The opportunity to work at the frontier of machine learning and global health, on a project with direct public health relevance.
- A position within a highly interdisciplinary international team spanning machine learning, statistics, genomics, epidemiology, and geography, with strong links to collaborators at UNC Chapel Hill.
- 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 dedicated career support for researchers as well as opportunities for promotion and progression.
- As a member of research staff you have 10 development days to use to develop your skills and explore your career prospects.
- 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 staff networks and resources to support your personal and professional wellbeing.
Further Information
Please note that this is a PhD level role but candidates who have not yet been officially awarded will be appointed as a Research Assistant.
The expected start date for this post is on 01st September 2026, and the contract end date will be on 31st August 2028 (a maximum of two-year contract).
If you require any further details about the role, please contact: Dr Elizaveta Semenova at e.semenova@imperial.ac.uk.
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