PhD Position Study Genetic Impacts on Brain Cells Using Single-Cell and Spatial ML Techniques

Join us to decode how genetic variation reprograms brain cells and disrupts their communication using AI.

PhD Position: Study Genetic Impacts on Brain Cells Using Single-Cell and Spatial ML Techniques

Job description

We are looking for a PhD student to work at the intersection of machine learning, single-cell genomics, and neurogenetics. Your project will focus on developing new methods to understand how genetic variants affect not only individual brain cells but also change the way cells interact and communicate — insights that are essential for understanding the cellular origins of brain disorders.

Despite major progress in genetics research, we still don’t know how genetic risk factors for brain disorders like schizophrenia, Alzheimer’s, and depression disrupt brain function. Genetic discoveries point to thousands of disease-associated SNPs, but most of them act in subtle and cell type–specific ways, and their downstream biological effects remain poorly understood.

This project tackles this fundamental gap by building computational models that simulate what goes wrong in the brain, one cell (and one cell–cell interaction) at a time.

You will work with large-scale single-cell and spatial transcriptomics data to develop and apply single-cell foundation models — generative machine learning models that represent the structure and variation of cell states. These models act as virtual cells simulating how perturbing the expression of genes altered by genetic variants affects the cell’s identity, behavior, and trajectory. You will extend these models to understand how genetic risk factors alter cell–cell communication networks. Spatial transcriptomics datasets will be used to anchor these models in real tissue context, revealing how spatially organized cell communities rewire under genetic perturbation.

Key challenges

• Use and improve single-cell foundation models to predict SNP-driven shifts in cell state and cell fate.
• Integrate spatial transcriptomics data to anchor these predictions in tissue context.
• Develop machine learning methods (e.g. graph neural networks, variational or diffusion models) to model cell–cell communication dynamics under genetic perturbation.
• Investigate how local interactions between perturbed and unperturbed cells reshape signaling networks and tissue states.
• Closely collaborate with neuroscientists in the BRAINSCAPES consortium to link model predictions to experimental and clinical relevance.

Benefits

• Shape next-generation models for understanding brain disease mechanisms.
• Work in a collaborative, interdisciplinary, and dynamic environment with leading experts in machine learning, computational biology, and neurogenomics.
• Access cutting-edge datasets, infrastructure, and computational and experimental facilities.
• Receive support for professional development and participation in international conferences.

Job requirements

• A Master’s degree in computational biology, machine learning, bioinformatics, AI, or a related field.
• Strong background in machine learning and data analysis.
• Interest in single-cell omics, spatial data, or systems neuroscience.
• Intellectual curiosity, independence, and motivation to tackle open-ended problems with real-world impact.
• Strong analytical thinking and problem-solving skills.
• A passion for using AI to answer fundamental questions in biology and medicine.
• Ability to work independently and as part of a multidisciplinary team.
• Strong interpersonal communication and collaboration abilities.
• Strong communication skills and proficiency in English.

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.

Faculty of Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.

BRAINSCAPES

BRAINSCAPES is a prestigious, nationally funded 10-year scientific program dedicated to mapping the biological mechanisms underlying multiple brain disorders. While genetic discovery studies have provided unprecedented insight into the genes associated with these disorders, the critical next step is to translate this knowledge into mechanistic understanding. BRAINSCAPES develops innovative analytical and experimental approaches to investigate how risk genes affect the function of specific cell types, neural circuits, and ultimately behavior. By uncovering the molecular and cellular basis of complex brain disorders, the program aims to pave the way for the development of novel, targeted treatments.

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 €3059 - €3881 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.

Additional information

This PhD position is positioned within the Delft Bioinformatics Lab, part of the Computer Science department of the Delft University of Technology under supervision of Prof. Marcel Reinders (m.j.t.reinders@tudelft.nl), and Ahmed Mahfouz from the Leiden University Medical Center (a.mahfouz@lumc.nl), in close collaboration with BRAINSCAPES scientists across the Netherlands.