PhD: Bayesian Modeling of Nanoparticle Transport in Tissue

Delft; Delft; On-site; EUR 36,000 - 45,000; Full time

Benefits offered by this job

Relocation support

Dual Career Programme

Flexible work hours

Health insurance discounts

Job summary

TU Delft seeks a PhD candidate to develop Bayesian, counterfactual models for nanoparticle transport in human tissue within the SYNERGIE project. You will work in a cross-disciplinary team including experts from Fraunhofer, Roche, Karolinska, and Maastricht University, contributing to an in silico platform and translational insights.

The role includes modeling, data calibration, and exploring minimal interventions to improve safety and regulatory relevance, with a January 2027 start date and

Qualifications

• MSc in applied mathematics, computational science, physics, systems biology, or a closely related quantitative field.
• Demonstrated experience building and solving ODE/dynamical systems models.
• Demonstrated experience with Bayesian inference in a probabilistic programming framework (PyMC, Stan or NumPyro).
• Strong scientific programming in Python; please point us to a repository.
• Excellent written and spoken English.

Responsibilities

• Build a mechanistic model of particle transport between nine tissues and calibrate it against experimental data using Bayesian inference.
• Determine which physical/chemical properties govern tissue distribution.
• Develop counterfactual methods to suggest minimal changes to improve safety/regulatory outcomes.
• Release the model as open-source software and support its use in regulatory dialogue.

Skills

ODE modeling

Bayesian inference

Python programming

English proficiency

Quantitative background

Education

MSc in a quantitative field

Tools

PyMC

Stan

NumPyro

Job description

TU Delft seeks a PhD candidate to develop Bayesian, counterfactual models for nanoparticle transport in human tissue within the SYNERGIE project. You will work in a cross-disciplinary team including experts from Fraunhofer, Roche, Karolinska, and Maastricht University, contributing to an in silico platform and translational insights.

The role includes modeling, data calibration, and exploring minimal interventions to improve safety and regulatory relevance, with a January 2027 start date and