Join TU Delft to develop generative AI methods for nanoparticle drug delivery design, at the intersection of machine learning, explainability, and pharmaceutical nanotechnology.Job description We are looking for a Postdoctoral Researcher to develop generative AI methods for nanoparticle (NP) drug delivery design. You will join the research group of Dr. Sepinoud Azimi, working within the NAP4DIVE project (Horizon Europe), a consortium including AstraZeneca, TU Eindhoven, University of Gothenburg, Chalmers, and FinnAdvance.
Nanoparticle drug delivery is a high-dimensional, multi-objective design problem: formulations consist of multiple interacting components whose therapeutic behaviour changes after administration due to biological interactions (protein corona formation, degradation, payload release). Current AI approaches treat NP design as static property prediction. This project takes a fundamentally different approach: using generative models to propose novel NP formulations and coupling them with explainability methods so that design decisions can be understood, validated, and trusted.
As a postdoc, you will:
- Develop generative AI models (e.g., variational autoencoders, diffusion models, or reinforcement learning-based optimization) for NP formulation design, targeting specific therapeutic outcomes such as blood-brain barrier permeability and tumour accumulation.
- Couple generative models with counterfactual explanation methods, enabling researchers and regulators to understand why a proposed formulation is predicted to work and what minimal design changes would alter therapeutic outcomes.
- Co-supervise doctoral candidates working on related topics, including nanoparticle database curation, molecular dynamics-based transport modelling, and reinforcement learning for treatment optimization.
- Contribute to high-impact publications.
You will work alongside PhD students and interact with experimental partners across the NAP4DIVE consortium. You will have access to the DelftBlue high-performance computing cluster.
This position offers a unique opportunity to shape an emerging field. The group is building toward a long-term research programme on trustworthy AI for personalized nanomedicine, and your contributions will directly feed into this vision.
The intended start date is July–August 2026.
Job requirements - PhD in machine learning, artificial intelligence, computational chemistry, computational materials science, or a closely related field.
- Demonstrated expertise in generative models for molecular or materials design, with at least one first-author publication using variational autoencoders, diffusion models, normalizing flows, or reinforcement learning-based design optimization.
- Strong programming skills in Python with experience in PyTorch, JAX, or equivalent deep learning frameworks.
- Ability to work independently, formulate research questions, and drive projects to publication.
- Excellent written and spoken English.
Preferred qualifications:
- Experience with drug delivery, nanomedicine, pharmaceutical formulation, or materials informatics.
- Familiarity with explainable AI or counterfactual explanation methods.
- Experience with molecular dynamics data, graph neural networks, or multi-component system modelling.
- Track record of interdisciplinary collaboration.
TU Delft (Delft University of Technology)Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.
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Faculty Technology, Policy and ManagementThe Faculty of TPM provides an important contribution to solving complex technical-social issues, such as energy transition, mobility, digitalisation, water management and (cyber) security. TPM does this with its excellent education and research at the intersection of technology, society and policy. We combine insights from both engineering and social sciences as well as the humanities. TPM develops robust models and designs, is internationally oriented and has an extensive network of knowledge institutions, companies, social organisations and governments.
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Conditions of employment - Duration of contract is 12 months Temporary
- A job of 36-40 hours per week.
- Salary and benefits are in accordance with the Collective Labour Agreement for Dutch
- An excellent pension scheme via the ABP.
- The possibility to compile an individual employment package every year.
- Discount with health insurers on supplemental packages.
- Flexible working week.
- Every year, 232 leave hours (at 38 hours). You can also sell or buy additional leave hours via the individual choice budget.
- Plenty of opportunities for education, training and courses.
- Partially paid parental leave
- Attention for working healthy and energetically with the vitality program.
Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit,
Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service 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.
Additional informationFor more information about this vacancy, please contact Dr. Sepinoud Azimi,
s.azimirashti@tudelft.nl.
Application procedureAre you interested in this vacancy? Please apply no later than
20 April 2026 via the application button and upload the following documents:
- CV.
- Motivational letter. In your cover letter, please describe (1) your experience with generative models and (2) a brief research idea for applying generative AI to nanoparticle design.
- A list of publications.
You can address your application to Sepinoud Azimi Rashti and Jolien Ubacht.
Please note: - You can apply online. We will not process applications sent by email and/or post.
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