Maria Papathanasiou
Posted Yesterday
PhD in Machine Learning-Accelerated Simulated Clinical Trials and Quantitative Systems Pharmacology Imperial College London in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
The post is advertised as a fully funded PhD opportunity, but the only explicit eligibility detail given is UK home fee status. No stipend amount or tuition breakdown is stated in the post.
Deadline
Nov 1, 2026
Country
United Kingdom
University
Imperial College London

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About this position
PhD opportunity in the Life Science and Process Systems Engineering Lab at the Department of Chemical Engineering, Imperial College London.
The project is titled Machine learning-accelerated simulated clinical trials and focuses on developing machine learning and probabilistic methods for uncertainty quantification of Quantitative Systems Pharmacology models. The goal is to make virtual clinical trials fast and reliable enough to support real drug development decisions, including dosing and trial design.
You will work closely with industry on real-world challenges in drug development and contribute to methods that can run efficiently across entire virtual patient populations. The post highlights recent related work with Roche and references project details and lab information for further reading.
Eligibility: open to students with UK home fee status only.
Funding: advertised as a fully funded PhD opportunity.
Deadline: round one deadline is 1 November.
Relevant study areas include machine learning, uncertainty quantification, probabilistic modelling, pharmacometrics, quantitative systems pharmacology, clinical trial simulation, and drug development.
Funding details
The post is advertised as a fully funded PhD opportunity, but the only explicit eligibility detail given is UK home fee status. No stipend amount or tuition breakdown is stated in the post.
What's required
Open to students with UK home fee status only. The project is for a PhD student and focuses on machine learning, probabilistic methods, uncertainty quantification, and quantitative systems pharmacology; interest in drug development and clinical trial modelling is relevant.
How to apply
Use the application link provided in the post to submit your PhD application. Review the project details and lab information first, then apply before the round one deadline of 1 November.
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