PhD Position Linking Gene Regulation to Neuronal Phenotype and Circuit Function

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profile Job Location:

Leuven - Belgium

profile Monthly Salary: Not Disclosed
Posted on: 6 hours ago
Vacancies: 1 Vacancy

Job Summary

About us

the VIB Center for AI & Computational Biology is a research center dedicated to integrating machine learning with deep biological insight to understand complex biological systems. Our mission is to move beyond descriptive biology and develop predictive mechanistic models that connect molecular regulation to cellular and systems-level phenotypes.

The Laboratory of Computational Biology in Leuven () led by Scientific Director Stein Aerts is seeking a highly motivated PhD candidate to study how gene-regulatory programs give rise to neuronal the context of the Methusalem BioMedAI ( this interdisciplinary project aims to bridge gene regulation neuronal cell types electrophysiology morphology and connectomics into a unified framework.

Neurons are traditionally classified based on transcriptional an chromatin accessibility profiles yet how these molecularly defined cell types relate to electrophysiological behavior and circuit integration remains poorly this project you will develop and apply spatial transcriptomics methods and combine these with measurements of brain activity and cellular morphology to directly link gene-regulatory cell states to functional neuronal phenotypes.

This ambitious project integrates wet-lab experimentation with advanced computational analysis and is ideal for a candidate eager to operate at the interface of molecular biology neuroscience and AI.

Responsibilities

Wet-Lab & Experimental Work

  • Set up and optimize imaging based spatial transcriptomics protocols.
  • Set up and optimize methods to measure neuronal activity and morphology.
  • Combine the two methods to detect the cell type and neuronal physiology in one experiment.

Computational & Data Analysis

  • Apply advanced image analysis to extract cellular morphology and spatial features.
  • Analyze multi-modal datasets combining transcriptomics chromatin accessibility imaging and electrophysiology.
  • Develop and apply machine learning approaches to link gene-regulatory programs to neuronal phenotypes.
  • Use explainable sequence-to-function models to interpret regulatory logic underlying neuronal identity and function.
  • Integrate molecular cell types with electrophysiological and neuronal connections.

Collaboration & Research Environment

  • Work in a highly interdisciplinary environment spanning AI genomics neuroscience and imaging.
  • Collaborate with experimental and computational scientists within VIB and partner institutions such as the labs of Pedro Goncalves and Maarten De Vos.
  • Present results at international conferences and contribute to high-impact publications.

Your profile

Education & Background

  • Masters degree in molecular biology biochemistry neuroscience bioengineering chemistry computational biology computer science or a related field.
  • Strong interest in both experimental biology and computational analysis.

Profile essentials

  • Background in molecular biology biochemistry and/or neuroscience.
  • Wet-lab experience.
  • Proficiency in Python.
  • Experience with data analysis machine learning and AI methods.
  • Motivation to tackle a challenging multi-disciplinary project.

Bonus (but not required)

  • Experience with spatial transcriptomics genomics or imaging-based methods.
  • Experience with image analysis single-cell or spatial omics data analysis.
  • Familiarity with machine learning frameworks (e.g. PyTorch TensorFlow)

Mindset

  • Curious self-motivated and eager to learn across disciplines.
  • Comfortable working at the interface of wet lab and computation.
  • Collaborative team player with strong communication skills.

Our Offer

  • Interdisciplinary Training: A unique opportunity to develop both wet-lab and computational expertise during your PhD.
  • Cutting-Edge Science: Work on fundamental questions linking gene regulation to neuronal function and circuits.
  • State-of-the-Art Infrastructure: Access to advanced sequencing imaging platforms and high-performance GPU computing.
  • Research Environment: An international collaborative and stimulating research setting at a top-tier university.
  • Supervision: Supervision by prof. Stein Aerts and Lars Borm (postdoc)
  • Funding: Fully funded PhD position (typically 4 years) with opportunities to apply for competitive fellowships.
  • Start Date: Flexible; as soon as possible

How to Apply

Please apply via the VIB online application system ( and include:

  • A motivation letter of 1-1.5 pages
  • A detailed CV including a brief summary of project work (thesis internships etc.)
  • University degree certificates

For informal inquiries about the project please contact: and

About us the VIB Center for AI & Computational Biology is a research center dedicated to integrating machine learning with deep biological insight to understand complex biological systems. Our mission is to move beyond descriptive biology and develop predictive mechanistic models that connect molecu...
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