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TU Delft

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

TU Delft Delft (10 km)
3.059 tot 3.881
38 - 40 uur

TU Delft

Assistant Professor in Environmental Psychology and Simulation

TU Delft
4.728 tot 6.433
38 uur
PhD

TU Delft

PhD Position Characterizing the Interiors of Icy Moons Using Integrated Geophysical Observations

TU Delft Delft (10 km)
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PhD

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TU Delft Delft (10 km)
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TU Delft
36 - 40 uur
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Assistant Professor: Self-Organizing Power Grids

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TU Delft
PhD Position Study Genetic Impacts on Brain Cells Using Single-Cell and Spatial ML Techniques
TU Delft Delft (10 km)
3.059 tot 3.881
38 - 40 uur
Status Open
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Wat wij vragen

Opleiding
A Master's degree in computational biology, machine learning, bioinformatics, AI, or a related field.
Ervaring
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.
Talen
  • Je beheerst Engels

Wat wij bieden

Salaris
€ 3.059 tot € 3.881
Uren
38 tot 40 uur per week
Dienstverband
fulltime
Type vacature
intern

Vacaturebeschrijving

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

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, 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 collobarate 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.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

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.

to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

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.

Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.

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, , and Ahmed Mahfouz from the Leiden University Medical Center, , in close collaboration with BRAINSCAPES scientists across the Netherlands.

Application procedure

  • An up-to-date and detailed curriculum vitae.
  • Copies of relevant academic transcripts.
  • A cover letter, which should summarize (1) why the applicant wants the position, (2) why the project is of interest to the applicant, (3) evidence of suitability for the job, and (4) what the applicant hopes to gain from the position.

You can address your application to Marcel Reinders and Ahmed Mahfouz.

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. For more details please check the Graduate Schools Admission Requirements.

Please note:

  • You can apply online. We will not process applications sent by email and/or post.
  • As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
  • Please do not contact us for unsolicited services.
Salarisomschrijving

Het salaris bedraagt €3059 - €3881

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