PhD Position Bayesian Modeling and Counterfactual Methods for Nanoparticle Transport in Human Tissue

Shape the future of nanoparticle safety and design. Join TU Delft as a PhD researcher using Bayesian and counterfactual modelling to predict nanoparticle transport in human tissue.

PhD Position Bayesian Modeling and Counterfactual Methods for Nanoparticle Transport in Human Tissue

Job description

We are looking for a PhD candidate to build the computational model at the center of a European project on nanoparticle transport in human tissue. You will join the research group of Dr. Sepinoud Azimi, working within the SYNERGIE project (Horizon Europe), a consortium of thirteen partners including Fraunhofer, Roche, the Karolinska Institute, University Hospital Aachen, Mimetas, Ruhr University Bochum and Maastricht University.

Small particles from the environment have been detected in human blood, placenta and brain tissue, but it is still not clear what they do there. Dose-response data for humans does not exist and animal studies have not transferred well, and as a result there is no exposure limit for these particles.

Part of the reason prediction is so hard is that a particle changes as it moves through the body. It acquires a layer of proteins, it aggregates with other particles, and depending on the material it may partly degrade, so that the particle reaching a given tissue is not the same object that was administered or characterised at the start. Most transport models do not account for this. They treat the particle as fixed, which means they are predicting the fate of something that has already changed.

The same difficulty affects engineered nanoparticles for drug delivery, and it is one of the reasons so few of them reach their intended target.

SYNERGIE is building a platform of nine human tissue-on-chip models that can be connected to follow a particle through uptake, circulation and storage. TU Delft leads the in silico work package.

As a PhD candidate, you will:

• Build a mechanistic model of how particles move between nine human tissues, and calibrate it against experimental data using Bayesian inference.
• Work out which physical and chemical properties of a particle decide where it ends up.
• Develop methods that go beyond prediction: for a particle that behaves badly, what is the smallest change that would fix it, and when should that answer not be trusted.
• Release the model as open-source software and support its use in regulatory dialogue.

You will also contribute to teaching in the department and to the supervision of BSc projects.

You will work alongside a postdoctoral researcher and PhD candidates on related problems, and interact with experimental partners across the SYNERGIE consortium. You will have access to the DelftBlue high-performance computing cluster.

The intended start date is January 2027.

Job requirements

• 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.
• Excellent written and spoken English.

Preferred qualifications:

• Continuous optimization or optimal control.
• Causal inference or counterfactual reasoning.
• Surrogate modelling, Gaussian processes, or emulation.
• Physiologically based pharmacokinetic modelling or systems pharmacology.
• Experience packaging and documenting scientific software.
• No background in toxicology, nanomaterials, chemistry or biology is required.

Conditions of employment

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from €3204–€4051 gross per month, from the first year to the fourth year based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! Coming to Delft Service offers information to help you prepare your relocation and organises events to help you settle in the Netherlands and expand your social network in Delft. A Dual Career Programme is available to support your accompanying partner with their job search in the Netherlands.

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis.

As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel to prevent the unwanted transfer of sensitive knowledge and technology. The assessment takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed.

This is an EU funded project, named SYNERGIE with project number 101288129 within European Union's Horizon Europe research and innovation program.

• Faculty: Faculty of Technology, Policy & Management.
• Hours per week: 36–40.