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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

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Country

United Kingdom

University

Imperial College London

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Keywords

Computer Science
Biomedical Engineering
Chemical Engineering
Uncertainty Analysis
Medical Science
Drug Development
Pharmacy
Statistics
Trial Design
ML

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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.

More information can be found here

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