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Delft University of Technology

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PhD Position: Bayesian Modeling and Counterfactual Methods for Nanoparticle Transport in Human Tissue Delft University of Technology in Netherlands

Degree Level

PhD

Field of study

Computer Science

Funding

PhD employment for 4 years in principle, with a salary of €3204–€4051 gross per month (years 1–4), plus 8% holiday allowance and an end-of-year bonus of 8.3%.

Deadline

Nov 29, 2026

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Country

Netherlands

University

Delft University of Technology

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Keywords

Computer Science
Biomedical Engineering
Mathematics
Computational Science
Python Programming
Causal Inference
Gaussian Processes
Bayesian Statistics
Dynamical Systems
Open-source Software
Surrogate Modeling
Statistics
Pharmacokinetic
Differential Equation
Physics

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About this position

At Delft University of Technology, this PhD project explores how nanoparticles move through human tissue and how their properties change along the way. The position sits in the SYNERGIE project, a Horizon Europe consortium focused on nanoparticle transport in human tissue and the safety and design of particles used in environmental and biomedical settings.

You will work in the research group of Dr. Sepinoud Azimi and contribute to the in silico work package led by TU Delft. The project is built around a platform of nine human tissue-on-chip models that can be connected to track a particle across uptake, circulation, and storage. Your task is to develop the computational model that links these tissues and to use it to study how particle properties influence where particles end up.

The research combines mechanistic modelling with Bayesian inference and counterfactual methods. You will build a model of particle transport between tissues, calibrate it against experimental data, and develop methods that can suggest what small change might improve the behaviour of a particle. The project also asks when such an answer should not be trusted, so the work includes uncertainty-aware analysis as well as prediction.

Alongside the core modelling work, you will help release the model as open-source software and support its use in regulatory dialogue. You will interact with experimental partners across the SYNERGIE consortium, work with a postdoctoral researcher and other PhD candidates, and have access to the DelftBlue high-performance computing cluster. The position is embedded in the Faculty of Technology, Policy and Management and the TU Delft Graduate School, within an international research environment.

The project is framed as a computational and methodological contribution to nanoparticle transport research, with applications to human tissue exposure and engineered nanoparticles for drug delivery.

Funding details

PhD employment for 4 years in principle, with a salary of €3204–€4051 gross per month (years 1–4), plus 8% holiday allowance and an end-of-year bonus of 8.3%.

What's required

MSc in applied mathematics, computational science, physics, systems biology, or a closely related quantitative field. Demonstrated experience building and solving ODE or dynamical systems models. Demonstrated experience with Bayesian inference in a probabilistic programming framework such as PyMC, Stan or NumPyro. Strong scientific programming in Python, with a repository to show your code. Excellent written and spoken English. Preferred qualifications include continuous optimization or optimal control, causal inference or counterfactual reasoning, surrogate modelling, Gaussian processes or emulation, physiologically based pharmacokinetic modelling or systems pharmacology, and experience packaging and documenting scientific software. No background in toxicology, nanomaterials, chemistry or biology is required.

How to apply

Apply online by 29 November 2026 via the application button. Upload your CV, a brief cover letter, a one-page research statement, and a link to a code repository you have built. If invited to interview, provide contact details for two referees with their consent.

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